DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . In the amendments of 07/16/2026, claims 2, 9, and 16 were cancelled. Thus, Claims 1, 3-8, 10-15, and 17-20 are still pending in this Application. The specification was amended.
Request for Continued Examination under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/16/2026 has been entered.
Response to Amendments/Remarks
Applicants’ arguments on page 9, with respect to objections to the Claims have been fully considered and they are respectfully persuasive. Therefore, objections to the claims have been withdrawn.
Applicant’s argument/remarks, on page 9, with respect to rejections to the claims under 35 USC § 112(a)-(b) have been fully considered and are persuasive. Therefore, rejections to the claims under 35 USC § 112(a)-(b) have been withdrawn.
Applicant’s argument/remarks, on pages 10-13, with respect to rejections to claims 1, 3-8, 10-15, and 17-20 under 35 USC § 103(a) have been fully considered but they are respectfully unpersuasive. However, the grounds of rejections to the claims have been changed based on the amendments which made the claims broader.
On page 12, the Applicant argues that:
“Ascoli discloses a memristor-based filter that requires external programming via pulse trains from a separate control circuit. Ascoli explicitly states that "a programming voltage source, responsible for the adaptation of the memristance, emits pulse trains with suitable shape on the basis of some input coming from a control circuit…
“Applicant has amended claim 1 to recite, in part: “wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance," and "wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter." Independent claims 8 and 15 include similar amendments. Applicant respectfully submits that the references, individually or in combination, fail to disclose or suggest the above features as recited in claim… Ascoli discloses a memristor-based filter that requires external programming via pulse trains from a separate control circuit. Ascoli explicitly states that "a programming voltage source, responsible for the adaptation of the memristance, emits pulse trains with suitable shape on the basis of some input coming from a control circuit…Ascoli's teachings are in direct contrast to the self-adaptive behavior recited in the amended claims. Critically, the claims now recite "wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance." This limitation requires that the memristance changes in direct response to the data signal flowing through the feedforward branch, so that the filter's passband adapts without any external intervention. In Ascoli, the opposite is true: the memristor's state is adjusted by an external control circuit that emits programming pulse trains, the reactive elements must be short-circuited during programming to prevent corruption of the memristor state, and the input signal must be kept small enough to prevent any change in memristor state”. These arguments are respectfully unpersuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
The invention as claimed is directed to the use of VIRTUAL low pass filter that includes a virtual memristor instead of a physical resistor, thus a virtual Memristive impedance or virtual memristive low pass filter, wherein a virtual Memristive impedance or virtual memristive low pass filter inherently act as a passband based on the nature of the memristor as admitted by the Applicant above “The memristor adapts its passband based on the signal flowing through it without requiring external programming pulses or auxiliary circuitry” (Applicant’s admitted statement)”. The disclosure does not teach or suggest that the novelty of the invention is the discovery of the Memristor or virtual memristor, or of a memristive LPF. Thus, it is assumed that these elements were very well known before the effective filing date of this Application.
The applicant’s argument above is directed to a physical memristive low pass filter. However, the claimed subject matter is directed to a virtual memristive LPF which is software based components which emulates or simulates the characteristics of a physical memristive low pass filter. When a virtual device is used, the virtual LPF will act as physical device including its inherent characteristics such as “having a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance”. Wang teaches the use of a virtual impedance to control the PWM of a converter system. Ascoli teaches the well-known memristive low pass filter and teaches the programming of the well-known memristive low pass filter for a specific intended use. Thus, Ascoli teaches a virtual impedance including a virtual memristive lows pass filter. Ascoli does not explicitly teach that the memristive low pass filter Ra and Rb resistances were tuned to be less than the switching frequency of the converter. However, Keshmiri and Price when combined with Ascoli and Wang teach a memristive low pass filter tuned to be less than the switching frequency of the converter” (see the rejection and see Keshmiri page 54 the memristor resistances Ra and Rb) and Price teaches tuning a filter to be less than a switching frequency of a converter (see price Col 7 lines 1-10and Col 10 claim 11, also, see the rejection in the final OA).
Thus, The Applicant arguments are directed to the programming of the Virtual Impedance by Ascoli and claims that they teach away from the amendments. These arguments are respectfully unpersuasive. In response to the arguments, the claims do not recite any specific step or process on how the virtual impedance was programmed. Thus, Ascoli programming of the filter parameter is irrelevant with respect to the claimed subject matter. As stated previously, when a virtual (software programmed) memristive LPF is used, it will inherently have the function of “wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance”. For instance, the Applicant’s (inventors) in the NPL reference “An Adaptive Virtual Impedance Control for Improving Power Sharing Among Inverters in Islanded AC Microgrids” previously provided and related to the claimed subject matter of the instant application discloses the programming and simulation of the virtual memristive LPF for testing their method or component. Ascoli perform the same simulation to teach how a virtual memristive LPF will act with respect to the input signals to be damped such as voltage or current of a power system.
On page 11 last par.- page 12 first par. , the Applicant further argues:
“Ascoli's filter is specifically designed so that the filtered signal does not alter the memristor state. The claimed virtual memristive impedance, by contrast, relies on the data flowing through it to drive the memristance change, producing the claimed self-adaptive passband. This is not an inherent property of all memristive filters; rather, it is a specific functional relationship between the feedforward data and the memristance that Ascoli affirmatively teaches away from. Accordingly, Ascoli fails to disclose or suggest the claimed virtual memristive impedance whose memristance varies automatically based on the first data flowing through it”. These arguments are respectfully unpersuasive.
Ascoli clearly teaches in table II on page 6, howe the memristor state changes based on an inputted signal. The feedforward data refers to the collected data such as a voltage or current. Wang teaches that virtual impedance receives a first data such as a voltage (see page 7020 Fig. 1 the virtual impedances are connected to a converter system; page 7027 Design of Inner Virtual Impedance Controller and see page 7028 Fig. 17 LPF-based inner virtual impedance controller for the converter current control loop. Fig. 17 shows a first data Vcf of a capacitor of the converter or the first data is the output of the controller Gvi,1(s), see page 28 Col 1 last par. “Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations, or be above the bandwidth of current control for mitigating harmonic instability).
On page 12, the Applicant further argues:
“Turning to Keshmiri, the Examiner relies on Keshmiri for the proposition that the
memristance value comprises a sum of a first value and a second value, citing the memristance equation RMEM(x) = RON·x + ROFF·(l-x). Applicant does not dispute that Keshmiri provides a mathematical model describing memristor resistance as a function of its doping state. However, Keshmiri is a study of memristor models and applications that provides generalized mathematical descriptions of physical memristor behavior. Keshmiri does not disclose or suggest a virtual memristive impedance operating in a feedforward branch of a power converter control system, nor does Keshmiri teach that a memristance varies automatically based on first data flowing through a virtual memristive impedance to produce a self-adaptive passband for the control system. Keshmiri supplies only a memristance model for a physical memristor device”. These arguments are unpersuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Keshmiri was cited to teach the inherent mathematical model used for programming a virtual memristor, wherein the model is a well-known model for the memristor as admitted by the Applicant in the arguments. One of ordinary in the art of programming and using virtual impedances would have been motivated to use the model of Keshmiri to program the memristor of an virtual Memristive LPF of Wang and Ascoli since these values are configurable and to have the inherent variable memristance.
On page 12, the Applicant further argues that:
“Turning to Price, the Examiner relies on Price for teaching that a cutoff frequency of a filter is set below a switching frequency of a power converter. See Price, Col. 7, lines 1-10. However, Price discloses a conventional resistor-based low-pass filter in a DC/DC converter whose cutoff frequency is fixed below the switching frequency to suppress high-frequency noise. Price's filter is not a memristive impedance of any kind; it is a standard analog filter with a static, fixed cutoff frequency that does not change in response to the signal passing through it. Price does not teach or suggest a virtual memristive impedance whose memristance "varies automatically based on the first data flowing through" the feedforward branch, producing a self-adaptive passband”. These arguments are unpersuasive.
Price was not cited to teach the virtual memristive LPF. Price was cited to teach the function of tuning the cutoff frequency of an impedance relative to a switching frequency of the power converter such that a low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter which is the main purpose of the LPF. As stated in the rejection, Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli- Keshmiri’s combination as taught above to include apply the teachings of Price such as setting the cut-frequency of the impedance at a value less than the switching frequency of the converter in the combination of Wang-Ascoli-Keshmiri including the virtual memristive impedance to set the cut-off frequency of their combination’s Memristive impedance relative or less than a switching frequency of the power converter to reduce the output ripple voltage which reduces the amplitude of the HF output ripple and may allow for automatic phase current balancing to take place as suggested by Price (see Col 7 lines 1-15).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3-7 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al (Virtual-Impedance-Based Control for Voltage-Source and Current-Source Converters”, 2015) in view Ascoli et al (“Memristor-based filtering applications, 2013; Cited in the IDS), Keshmiri (“A Study of the Memristor Models and Applications”, 2014), and Price et al (US 10128758).
As per claim 1, Wang teaches a method comprising:
receiving, by a control system (see page 7021 Col 1 last par, “…where Ts is the sampling period of the control system….”; also, see page 7030 “A multisampling (at 3024 Hz) method is used to reduce the effects of time delays associated with such a low switching frequency; also, see 7030 Col 2 last par “…which has a switching frequency of 540 Hz. Space vector PWM …”) where Ts is the sampling period of the control system) and from a power converter, first data associated with operation of the power converter (see page 7020 Fig. 1 the virtual impedances are connected to a converter system; page 7027 Design of Inner Virtual Impedance Controller and see page 7028 Fig. 17 LPF-based inner virtual impedance controller for the converter current control loop. Fig. 17 shows a first data Vcf of a capacitor of the converter or the first data is the output of the controller Gvi,1(s), see page 7028 Col 1 last par. “Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations, or be above the bandwidth of current control for mitigating harmonic instability”), wherein the first data is received over a feedforward branch including a virtual(see page 7027 Design of Inner Virtual Impedance Controller and see Fig. 17 LPF-based inner virtual impedance controller for the converter current control loop. Fig. 17 shows a first data Vcf of a capacitor of the converter; see page 7026 col1 last par. “…the filter capacitor voltage VCf…”),
wherein the(see Fig. 17 page 7028, a filter is usually inherently associated with a transfer function, in this case is Fvi 1(s),
wherein the virtual a virtual (see page 7028 Col 1 last par. “Besides these basic controllers, the LPF [26] … can also be used. Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations),
sending, by the control system and to the power converter, a first output signal indicating a switching pattern for the power converter, (see Fig. 17 and see 7028 Col 1 last paragraph “Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations, or be above the bandwidth of current control for mitigating harmonic instability….”, Fig. 17 GD(s) represents the transfer function of modulated current producing a modulated output which can be the first output signal or Yps controller outputs a signal which can be considered the output signal; also, see Fig. 1 the signal is a PWM signal for switching a VSC), wherein the first output signal is based on an output from the virtual (see Fig. 17 and Fig. 18 and Fig. 19 ).
However, Wang does not explicitly teach:
including a virtual memristive impedance operating as a self-adaptive passband for the control system to achieve stable performance of the power converter under parameter variation,
wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance,
the virtual memristive impedance is associated with a transfer function (hf),
wherein the transfer function comprises a memristance value,
wherein the memristance value comprises a sum of a first value and a second value,
wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a switching frequency of the power converter by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise,
wherein the second value is selected such that the cutoff frequency of the virtual memristive impedance when doped is less than a switching frequency of the power converter by a second amount (0018 RA), and wherein the second amount is greater than the first amount,
wherein the virtual memristive impedance includes a virtual memristor that is implemented in control logic,
wherein the virtual memristive impedance is a virtual memristive low pass filter, and
wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter;
wherein the first output signal is based on an output from the virtual memristor to enhance stability of the power converter.
However, Ascoli teaches a virtual memristive impedance, wherein the virtual memristive impedance is a virtual memristive low pass filter (see Fig. 4 memristive impedance is a low pass filter MC filter; also, see page 1 Col 2 pars. 2-3 “…A memristor-based filter may be easily derived from its resistor based counterpart by simply replacing each resistor with a memristor…Two simple memristor-based filters with adaptable frequency response, specifically a first-order low-pass filter with tunable cut-off frequency and a second-order band-pass filter with tunable quality factor, are designed and their proper functioning is thoroughly validated. This work represents the first step towards a modular design of memristor-based analog filters”; also, see page 3 last par. “This section shall derive the memristor-based adaptable versions of a couple of basic classical analog filters [10] , specifically a first-order low-pass filter with tunable cut-off frequency… We shall first consider a modified version of the basic first order R-C low-pass filter, where the resistor is replaced by a memristor. The resulting circuit , usually referred to as an M- C low-pass filter, is shown in Fig. 4,”), operating as a self-adaptive passband for the control system to achieve stable performance of a system under parameter variation, (see page 1 Col 2 pars. 2-3; also, see page 3 Col 2 A . “First- order M- C filter with tunable cut- off frequency… Let us design a filter with tunable cut-off frequency expressed by We = Wx) . It is worthy to note that the amplitude of the filter input signal Vi should be chosen sufficiently small so as
to prevent any unwanted change in memristor state… the boundary conditions and parameters D and j.l are kept unvaried. The on and off resistance of the memristor are respectively set to Ron = 100 n (as a result k = 104 C) and Raf f = 6000 n. Under this parameter setting the cut-off frequency of the filter may
assume values within closed interval [26. 5258 Hz, 1 . 5915 kH z] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…”, the memristor acts as a self-adaptive passband based on the current/voltage that causes doping of the memristor, thus, changing the voltage/current input will cause the Memristor to cause a hysteresis in the resistances which results in the cutting frequency to change), wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance (see page 1 Col 2 pars. 2-3; see page 2 Col 2 par. 2 “Fig. 2 shows for each value of delta tp how the memristor state vo (t) (plot (b) ) and the memristance R(t) (plot (a) ) evolve with time. As expected, when the input voltage across the memristor returns to 0, state and memristance remain constant for all subsequent time instants…”, Thus, the memristance varies automatically based on the data flowing through the impedance or memristor. This is an inherent function of memristor which changes dynamically and automatically based on the input signal such as voltage, also, see page 3 Col 2 “A… The on and off resistance of the memristor are respectively set to Ron = 100 n (as a result k = 104 C) and Raf f = 6000 n. Under this parameter setting the cut-off frequency of the filter may
assume values within closed interval [26. 5258 Hz, 1 . 5915 kH z] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…”, the memristor acts as a self-adaptive passband based on the current/voltage that causes doping of the memristor, thus, changing the voltage/current input will cause the Memristor to cause a hysteresis in the resistances which results in the cutting frequency to change), the virtual memristive impedance is associated with a transfer function (hf), wherein the transfer function comprises a memristance value (the inherent transfer function of an MC filter is 1/ (1 + JwRmC), wherein Rm is the Memristance of a memristor; see page 3 Col 2 “First- order M- C filter with tunable cut- off frequency We shall first consider a modified version of the basic first order… The resulting circuit , usually referred to as an M-C low-pass filter, is shown in Fig. 4, where Vi and Vo respectively denote the filter input and output voltages, and the memristor circuit of Fig. 1 is replaced with its symbol (note the position of nodes y and z… Let us first focus our attention on the first-order low-pass filter of Fig. 1 . The capacitance is set to C = 1mu F. The BCM PSpice circuit of Fig. 1 models the memristor… The on and off resistance of the memristor are respectively set to Ron = 100 ohms (as a result k = 104 C) and Roff = 6000 ohms. Under this parameter setting the cut-off frequency of the filter may assume values within closed interval [26. 5258 Hz, 1 . 5915 kHz] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…); also, see page 4 Col 1 last 6 lines “With reference to Fig. 5(a) , taking the values Vej the memristor state assumes at start (j = 0) and during the time intervals between each pair of consecutive programming pulses (j = 1 , 2 , 3 , 4, 5 , 6 , 7) , the filter transfer function is computed for each memristor state value by means of an Alternating Current (AC) Analysis-based simulation (see Fig. 6, where the)), wherein the memristance value comprises a first value and a second value, and wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a frequency by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise, wherein the second value is selected such that the cutoff frequency of the memristive impedance is less than a frequency by a second amount when doped, and wherein the second amount is greater than the first amount (see page 3 Col 2 “…Under this parameter setting the cut-off frequency of the filter may assume values within closed interval [26. 5258 Hz, 1 . 5915 kHz] (the lower an upper limit respectively refer to the largest and smallest possible memristance values… The on and off resistance of the memristor are respectively set to Ron = 100 ohms (as a result k = 104 C) and Roff = 6000 ohms” and see page 4 Col 1 last 6 lines “With reference to Fig. 5(a) , taking the values Vej the memristor state assumes at start (j = 0) and during the time intervals between each pair of consecutive programming pulses (j = 1 , 2 , 3 , 4, 5 , 6 , 7) , the filter transfer function is computed for each memristor state value by means of an Alternating Current (AC) Analysis-based simulation (see Fig. 6, where the…”; also, see page 5 Col 1 last paragraph “The memristor on and off resistances are chosen as Ron = 10 ohms (as a result , k = 103 C- I ) and Roff = 1000 ohms respectively”, Ron and Roff are equivalent to RA and RB. The values when doped correspond to the filter receiving a current value or being doped with ions/charge. Thus, Ra and Rb will cause the memristor filter to achieve a band of cutting frequency which will be less than the desired output frequency), wherein the memristive impedance includes a virtual memristor that is implemented in control logic (see page 3 “The capacitance is set to C = 1mu F. The BCM PSpice circuit of Fig. 1 models the memristor”, A PSpice refers to software/control logic/program that is used to implement the memristor as a virtual memristor or software based memristor; also, see page 4 Col 1 par. 2 “…During the programming phases
the memristance is adjusted as specified by the control circuitry. When the memristor state increases (decreases) , the bandwidth of the filter gets larger (smaller) . This implies an increase (decrease) in the amplitude of the filter output voltage under the applied sine waveform…”; also, see page 5 Col 1 par. 2 “…The
capacitance Cx in the memristor emulator of Fig. 1 is chosen…”; also, see page 6 the conclusion “…a first-order low-pass filter with tunable cutoff frequency and a second-order band-pass filter with tunable quality factor (where parameter tuning depends on the memductance of the memristor) , were designed and analyzed
through computer simulations of a PSpice-based BCM emulator…”), wherein an output signal is based on an output from the virtual memristor to enhance stability of an output signal (see page 5 Col 1 the table shows outputs; also, se Fig. 5).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang’s invention to include a virtual memristive impedance, wherein the virtual memristive impedance is a virtual memristive low pass filter, operating as a self-adaptive passband for the control system to achieve stable performance of a system under parameter variation, wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance, the virtual memristive impedance is associated with a transfer function (hf), wherein the transfer function comprises a memristance value, wherein the memristance value comprises a first value and a second value, wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a frequency by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise, wherein the second value is selected such that the cutoff frequency of the virtual memristive impedance is less than a frequency by a second amount when doped, and wherein the second amount is greater than the first amount, wherein the memristive impedance includes a virtual memristor that is implemented in control logic, wherein an output signal is based on an output from the virtual memristor to enhance stability of the output signal as taught by Ascoli in order to provide a virtual impedance such as LPF MC filter since these components are programmable and their cutoff frequency is tunable and dynamically changed and its properties are time variant (Analog RC-LPF circuits are constant and time invariant while MC-LPF are time variants and can be tuned; see page 2 Col 2 MC filter with tunable cutoff frequency), also, applying a virtual memristor based virtual impedance to the system Wang will result in an output signal with an adaptive range and enhanced stability output signal.
Ascoli teaches that the Memristor has parameters such as Ron and Roff, associated with a Memristance, which are equivalent to lower and upper limits of resistance values, and teaches that the Memristor are fabricated by HP labs, thus, Wang-Ascoli teach a first order memristor based low pass filter MC filter, wherein the inherent transfer function of a Memristive MC filter is 1/ (1 + JwRmC), wherein Rm is the Memristance of a memristor, but Wang-Ascoli does not explicitly defines or exemplifies the Memristance, and thus, Wang-Ascoli does not explicitly teach wherein the memristance value comprises a sum of a first value and a second value, and wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter.
However, Keshmiri teaches a memristor comprising a memristance value defined by a sum of a first value and a second value (see page 54 equation 47 and page 91 equation 73; also, see page 95 equation 81 RMEM ( x)= RON x + ROFF (1− x), , wherein the first value includes a product of a first memristance value and a weight value (RON x), and wherein the second value includes a product of a second memristance value and the weight value (see page 54 equation 47 and page 91 equation 73; also, see page 68 par. 1; also, see page 95 equation 81 ROFF (1− x)), and the first value and second value corresponds to doped and undoped values (see page 95 7.3 “where the sum of resistances of both the doped and undoped regions of the device gives the total resistance, as shown in (81).”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli invention to include a transfer function associated with the memristive impedance (see Wang-Ascoli teach a first order MC low pass filter which inherently includes a transfer function 1/ (1 + JwRmC)) comprising a memristive value comprising a sum of a first value and a second value, wherein the first value includes a product of a first memristance value and a weight value, and wherein the second value includes a product of a second memristance value and the weight value, d the first value and second value corresponds to doped and undoped values as taught by Keshmiri by including a memristor with a memristance defined as RMEM ( x)= RON x+ ROFF (1− x)) because Memristors have the capacity of storing the resistance a (see page 45 the Memristor; and see page 47) and are configurable and time variant.
While the cut-off frequency of the memristive impedance is an inherent characteristic of the component/circuit (cut-off frequency Fc of memristor filter is found by Fc = 1/ 2ΠMkC, where Mk = ɑRA + (1- ɑ)RB), and Ascoli teaches the selection of the values of the resistances RA and RB of the memristor to obtain a desired cut-off frequency, Wang-Ascoli-Keshmiri still does not explicitly teach wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter.
However, Price teaches a voltage converter comprising an impedance or low pass filter (see Col 6 line 62-63 “the HF filter 412 may be a first order low-pass filter), wherein the cutoff frequency of the impedance is tuned relative to a switching frequency of the power converter such that the low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter (the term relative is interpreted in the BRI in light of the disclosure as “less than a switching frequency of the converter”; see Price Col 7 line 1-10 “…the cutoff frequency (e.g., the −3 dB frequency) for the HF filter 412 may be set below the switching frequency of the DC/DC converter 100, …For example, with a converter switching frequency of 140 MHz and a 0 dB crossover frequency for the error amplifier 410 of 1.7 MHz, a filter frequency of 25 MHz may be used to suppress frequencies of signal components that would otherwise sneak through the error amplifier 410 and allow the individual phase drive signals to be generated with the desired phase shifts” ; also, see Col 10 Claim 11).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli- Keshmiri’s combination as taught above to include wherein the cutoff frequency of the impedance is tuned relative to a switching frequency of the power converter such that the low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter as taught by Price in order to reduce or suppress frequencies found in the output signal and also to reduce the output ripple voltage which reduces the amplitude of the HF output ripple and may allow for automatic phase current balancing to take place (see Col 7 lines 1-15) and apply the teachings of Price such as setting the cut-frequency of the impedance at a value less than the switching frequency of the converter in the combination of Wang-Ascoli-Keshmiri including the virtual memristive impedance to set the cut-off frequency of their combination’s Memristive impedance relative or less than a switching frequency of the power converter to reduce the output ripple voltage which reduces the amplitude of the HF output ripple and may allow for automatic phase current balancing to take place as suggested by Price (see Col 7 lines 1-15).
As per claim 3, Wang-Ascoli-Keshmiri-Price teaches the method of claim 1, further comprising: Wang further teaches receiving, by the control system, a reference value (see Fig. 17 reference current iLf);
receiving, by the control system and from the power converter, second data (see Fig. 17 measured current iLf; also, see page 7026 Col 2 par. 5 “… The converter
current iLf ,..”); and
calculating, by the control system, a first difference between the reference value and the second data from the power converter (see Fig. 17
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).
As per claim 4, Wang-Ascoli-Keshmiri-Price teaches the method of claim 3, Wang further teaches wherein the first difference represents an error value associated with the power converter (see Fig. 17 measured current iLf; also, see page 7026 Col 2 par. 5 “… The converter current iLf ,..”
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), and
wherein the method further comprises:
determining, by the control system, an error compensated output value based on an error compensation performed using the error value (see Fig. 17 Gci(s) and see 7020 Col 1 last par. “The grid current ig is controlled by a current controller Gci(s)…”); and
determining, by the control system, a summation of the error compensated output value and the first data to produce a second output value (see Fig. 17 the output of GCi and the output if the virtual impedance Gvi, 1(s) are summed
PNG
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200
400
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),
wherein the first output signal from the control system to the power converter is based on the second output value (see Fig. 17).
As per claim 5, Wang-Ascoli-Keshmiri-Price teaches the method of claim 1, Ascoli teaches that the Memristor has parameters such as Ron and Roff with are equivalent to lower and upper limits of resistance values, and teaches that the Memristor are fabricated by HP labs, and Wang-Ascoli teach a first order memristor based low pass filter MC filter, wherein the inherent transfer function of a MC filter is 1/ (1 + JwRmC), wherein Rm is the Memristance of a memristor, however, Wang-Ascoli does not define the equation of Rm, and thus, Wang-Ascoli does not explicitly teach wherein the transfer function associated with the virtual memristive impedance further comprises a product of first value and a weight and a product of the second value and a difference between a third values and the weight value.
However, Keshmiri further teaches a memristor comprising a memristance comprises a product of first value and a weight and a product of the second value and a difference between a third values and the weight value (see page 54 equation 47 and page 91 equation 73; also, see page 95 equation 81 RMEM ( x)= RON x + ROFF (1− x)).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang’s combination as taught above to include a transfer function associated with the memristive impedance further comprises a memristance that comprises a product of first value and a weight and a product of the second value and a difference between a third values and the weight value as taught by Keshmiri by including a memristor with a memristance defined as RMEM ( x)= RON x+ ROFF (1− x) because Memristors have the capacity of storing the resistance a (see page 45 the Memristor; and see page 47) and are configurable and time variant.
As per claim 6, Wang-Ascoli-Keshmiri-Price teaches the method of claim 1, Wang further teaches wherein the first output signal is a pulse-width modulated (PWM) signal (see Fig. 17 Vm is a modulated signal).
Wang further teaches Fig.1 an inner virtual impedance with a PWM generator (see Fig. 1 and see page 7020 col 2 par. 1 “The inner virtual impedance Zvi(s), which is directly applied to the PWM modulator and is, thus, influenced by the time delays of the digital control system”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli’s combination as taught above to include an inner virtual impedance with a PWM generator to generate the first output signal as a pulse-width modulated (PWM) signal as taught by Wang in order to control the converter (see Figs. 1-2).
As per claim 7, Wang-Ascoli-Keshmiri-Price teaches the method of claim 1, Wang further teaches wherein the first data comprises at least one of: a voltage signal associated with a capacitor of the power converter and a current signal associated with an inductor of the power converter (see Fig. 17 Vcf, and see page 7036 last par. “…where the filter capacitor voltage VCf…”).
Claim(s) 8, 10-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al (Virtual-Impedance-Based Control for Voltage-Source and Current-Source Converters”, 2015) in view Ascoli et al (“Memristor-based filtering applications, 2013; Cited in the IDS), Keshmiri (“A Study of the Memristor Models and Applications”, 2014), Price et al (US 10128758) and Hartman et al (US 20200358353, cited in the IDS)).
As per claim 8, Wang teaches a system comprising:
A power converter (see Fig. 1 power converter); and
a control system (see Fig. 1 control system comprising control components) comprising:
receive, from a power converter, first data associated with operation of the power converter (see page 7020 Fig. 1 the virtual impedances are connected to a converter system; page 7027 Design of Inner Virtual Impedance Controller and see page 7028 Fig. 17 LPF-based inner virtual impedance controller for the converter current control loop. Fig. 17 shows a first data Vcf of a capacitor of the converter or the first data is the output of the controller Gvi,1(s), see page 28 Col 1 last par. “Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations, or be above the bandwidth of current control for mitigating harmonic instability”), wherein the first data is received over a feedforward branch including a virtual (see page 7027 Design of Inner Virtual Impedance Controller and see Fig. 17 LPF-based inner virtual impedance controller for the converter current control loop. Fig. 17 shows a first data Vcf of a capacitor of the converter; see page 7026 col1 last par. “…the filter capacitor voltage VCf…”),
wherein the virtual (see Fig. 17 page 7028, a filter is usually inherently associated with a transfer function, in this case is Fvi 1(s),
perform, by to the power converter, switching actions based on a first output signal received from the control system (see Fig. 17 and see 7028 Col 1 last paragraph “Fig. 17 illustrates an LPF in Gvi,1 (s) within the capacitor voltage feedback for stabilizing the converter current control loop [26], where the LPF cutoff frequency can be below one-tenth of the bandwidth of current control loop for damping subsynchronous oscillations, or be above the bandwidth of current control for mitigating harmonic instability….”, Fig. 17 GD(s) represents the transfer function of modulated current producing a modulated output which can be the first output signal or Yps controller outputs a signal which can be considered the output signal; also, see Fig. 1 the signal is a PWM signal for switching a VSC), wherein the first output signal is based on an output from the virtual (see Fig. 17 and Fig. 18 and Fig. 19 ).
However, Wang does not explicitly teach including one or more processors operable to execute a set of computer-executable instructions; and memory operable to store the set of computer-executable instructions operable to:
including a virtual memristive impedance operating as a self-adaptive passband for the control system to achieve stable performance of the power converter under parameter variation,
wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance,
wherein the virtual memristive impedance is associated with a transfer function (hf),
wherein the transfer function comprises a memristance value,
wherein the memristance value comprises a sum of a first value and a second value,
wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a switching frequency of the power converter by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise, wherein the second value is selected such that the cutoff frequency of the virtual memristive impedance when doped is less than a switching frequency of the power converter by a second amount, and wherein the second amount is greater than the first amount,
wherein the virtual memristive impedance includes a virtual memristor that is implemented in control logic,
wherein the virtual memristive impedance is a virtual memristive low pass filter,
wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter;
wherein the first output signal is based on an output from the virtual memristor to enhance stability of the power converter.
However, Ascoli teaches a virtual memristive impedance, wherein the virtual memristive impedance is a virtual memristive low pass filter (see Fig. 4 memristive impedance is a low pass filter MC filter; also, see page 1 Col 2 pars. 2-3 “…A memristor-based filter may be easily derived from its resistor based counterpart by simply replacing each resistor with a memristor…Two simple memristor-based filters with adaptable frequency response, specifically a first-order low-pass filter with tunable cut-off frequency and a second-order band-pass filter with tunable quality factor, are designed and their proper functioning is thoroughly validated. This work represents the first step towards a modular design of memristor-based analog filters”; also, see page 3 last par. “This section shall derive the memristor-based adaptable versions of a couple of basic classical analog filters [10] , specifically a first-order low-pass filter with tunable cut-off frequency… We shall first consider a modified version of the basic first order R-C low-pass filter, where the resistor is replaced by a memristor. The resulting circuit , usually referred to as an M- C low-pass filter, is shown in Fig. 4,”), operating as a self-adaptive passband for the control system to achieve stable performance of a system under parameter variation (see page 1 Col 2 pars. 2-3; also, see page 3 Col 2 A . “First- order M- C filter with tunable cut- off frequency… Let us design a filter with tunable cut-off frequency expressed by We = Wx) . It is worthy to note that the amplitude of the filter input signal Vi should be chosen sufficiently small so as
to prevent any unwanted change in memristor state… the boundary conditions and parameters D and j.l are kept unvaried. The on and off resistance of the memristor are respectively set to Ron = 100 n (as a result k = 104 C) and Raf f = 6000 n. Under this parameter setting the cut-off frequency of the filter may
assume values within closed interval [26. 5258 Hz, 1 . 5915 kH z] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…”, the memristor acts as a self-adaptive passband based on the current/voltage that causes doping of the memristor, thus, changing the voltage/current input will cause the Memristor to cause a hysteresis in the resistances which results in the cutting frequency to change ), wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance (see page 1 Col 2 pars. 2-3; see page 2 Col 2 par. 2 “Fig. 2 shows for each value of delta tp how the memristor state vo (t) (plot (b) ) and the memristance R(t) (plot (a) ) evolve with time. As expected, when the input voltage across the memristor returns to 0, state and memristance remain constant for all subsequent time instants…”, Thus, the memristance varies automatically based on the data flowing through the impedance or memristor. This is an inherent function of memristor which changes dynamically and automatically based on the input signal such as voltage, also, see page 3 Col 2 “A… The on and off resistance of the memristor are respectively set to Ron = 100 n (as a result k = 104 C) and Raf f = 6000 n. Under this parameter setting the cut-off frequency of the filter may
assume values within closed interval [26. 5258 Hz, 1 . 5915 kH z] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…”, the memristor acts as a self-adaptive passband based on the current/voltage that causes doping of the memristor, thus, changing the voltage/current input will cause the Memristor to cause a hysteresis in the resistances which results in the cutting frequency to change), the virtual memristive impedance is associated with a transfer function (hf), wherein the transfer function comprises a memristance value, (the inherent transfer function of an MC filter is 1/ (1 + JwRmC), wherein Rm is the Memristance of a memristor; see page 3 Col 2 “First- order M- C filter with tunable cut- off frequency We shall first consider a modified version of the basic first order… The resulting circuit , usually referred to as an M-C low-pass filter, is shown in Fig. 4, where Vi and Vo respectively denote the filter input and output voltages, and the memristor circuit of Fig. 1 is replaced with its symbol (note the position of nodes y and z… Let us first focus our attention on the first-order low-pass filter of Fig. 1 . The capacitance is set to C = 1mu F. The BCM PSpice circuit of Fig. 1 models the memristor… The on and off resistance of the memristor are respectively set to Ron = 100 ohms (as a result k = 104 C) and Roff = 6000 ohms. Under this parameter setting the cut-off frequency of the filter may assume values within closed interval [26. 5258 Hz, 1 . 5915 kHz] (the lower an upper limit respectively refer to the largest and smallest possible memristance values…); also, see page 4 Col 1 last 6 lines “With reference to Fig. 5(a) , taking the values Vej the memristor state assumes at start (j = 0) and during the time intervals between each pair of consecutive programming pulses (j = 1 , 2 , 3 , 4, 5 , 6 , 7) , the filter transfer function is computed for each memristor state value by means of an Alternating Current (AC) Analysis-based simulation (see Fig. 6, where the)), wherein the memristance value comprises a first value and a second value, and wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a frequency by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise, wherein the second value is selected such that the cutoff frequency of the virtual memristive impedance is less than a frequency by a second amount when doped, and wherein the second amount is greater than the first amount (see page 3 Col 2 “…Under this parameter setting the cut-off frequency of the filter may assume values within closed interval [26. 5258 Hz, 1 . 5915 kHz] (the lower an upper limit respectively refer to the largest and smallest possible memristance values… The on and off resistance of the memristor are respectively set to Ron = 100 ohms (as a result k = 104 C) and Roff = 6000 ohms” and see page 4 Col 1 last 6 lines “With reference to Fig. 5(a) , taking the values Vej the memristor state assumes at start (j = 0) and during the time intervals between each pair of consecutive programming pulses (j = 1 , 2 , 3 , 4, 5 , 6 , 7) , the filter transfer function is computed for each memristor state value by means of an Alternating Current (AC) Analysis-based simulation (see Fig. 6, where the…”; also, see page 5 Col 1 last paragraph “The memristor on and off resistances are chosen as Ron = 10 ohms (as a result , k = 103 C- I ) and Roff = 1000 ohms respectively”, Ron and Roff are equivalent to RA and RB. The values when doped correspond to the filter receiving a current value or being doped with ions/charge. Thus, Ra and Rb will cause the memristor filter to achieve a band of cutting frequency which will be less than the desired output frequency), wherein the virtual memristive impedance includes a virtual memristor that is implemented in control logic (see page 3 “The capacitance is set to C = 1mu F. The BCM PSpice circuit of Fig. 1 models the memristor”, A PSpice refers to software/control logic/program that is used to implement the memristor as a virtual memristor or software based memristor; also, see page 4 Col 1 par. 2 “…During the programming phases the memristance is adjusted as specified by the control circuitry. When the memristor state increases (decreases) , the bandwidth of the filter gets larger (smaller) . This implies an increase (decrease) in the amplitude of the filter output voltage under the applied sine waveform…”; also, see page 5 Col 1 par. 2 “…The capacitance Cx in the memristor emulator of Fig. 1 is chosen…”; also, see page 6 the conclusion “…a first-order low-pass filter with tunable cutoff frequency and a second-order band-pass filter with tunable quality factor (where parameter tuning depends on the memductance of the memristor) , were designed and analyzed through computer simulations of a PSpice-based BCM emulator…”), wherein an output signal is based on an output from the virtual memristor to enhance stability of an output signal (see page 5 Col 1 the table shows outputs; also, se Fig. 5).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang’s invention to include a virtual memristive impedance, wherein the virtual memristive impedance is a virtual memristive low pass filter, operating as a self-adaptive passband for the control system to achieve stable performance of a system under parameter variation, wherein a memristance of the virtual memristive impedance varies automatically based on the first data flowing through the virtual memristive impedance, the virtual memristive impedance is associated with a transfer function (hf), wherein the transfer function comprises a memristance value, wherein the memristance value comprises a first value and a second value, and wherein the first value is selected such that a cutoff frequency of the virtual memristive impedance when undoped is less than a frequency by a first amount to capture a ramp-up during a transient period while attenuating high-frequency noise, wherein the second value is selected such that the cutoff frequency of the virtual memristive impedance is less than a frequency by a second amount when doped, and wherein the second amount is greater than the first amount, wherein an output signal is based on an output from the virtual memristor to enhance stability of the output signal as taught by Ascoli in order to provide a virtual impedance such as LPF MC filter since these components since these components are programmable and their cutoff frequency is tunable and dynamically changed and its properties are time variant (Analog RC-LPF circuits are constant and time invariant while MC-LPF are time variants and can be tuned; see page 2 Col 2 MC filter with tunable cutoff frequency), also, applying a memristor based virtual impedance to the system Wang will result in an output signal with an adaptive range and enhanced stability output signal.
Ascoli teaches that the Memristor has parameters such as Ron and Roff, associated with a Memristance, which are equivalent to lower and upper limits of resistance values (RA and RB), and teaches that the Memristor are fabricated by HP labs, Wang-Ascoli teach a first order memristor based low pass filter MC filter, wherein the inherent transfer function of a Memristive MC filter is 1/ (1 + JwRmC), wherein Rm is the Memristance of a memristor, but Wang-Ascoli does not explicitly defines or exemplifies the Memristance, and thus, Wang-Ascoli does not explicitly teach wherein the memristance value comprises a sum of a first value and a second value, and a cutoff frequency of the memristive impedance is less than a switching frequency of the power converter by a first amount when undoped and by a second amount when doped, and wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter.
However, Keshmiri teaches a memristor comprising a memristance value defined by a sum of a first value and a second value (see page 54 equation 47 and page 91 equation 73; also, see page 95 equation 81 RMEM ( x)= RON x + ROFF (1− x), , wherein the first value includes a product of a first memristance value and a weight value (RON x), and wherein the second value includes a product of a second memristance value and the weight value (see page 54 equation 47 and page 91 equation 73; also, see page 68 par. 1; also, see page 95 equation 81 ROFF (1− x)), and the first value and second value corresponds to doped and undoped values (see page 95 7.3 “where the sum of resistances of both the doped and undoped regions of the device gives the total resistance, as shown in (81).”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli invention to include a transfer function associated with the memristive impedance (see Wang-Ascoli teach a first order MC low pass filter which inherently includes a transfer function 1/ (1 + JwRmC)) comprising a memristive value comprising a sum of a first value and a second value, wherein the first value includes a product of a first memristance value and a weight value, and wherein the second value includes a product of a second memristance value and the weight value, the first value and second value corresponds to doped and undoped values as taught by Keshmiri by including a memristor with a memristance defined as RMEM ( x)= RON x+ ROFF (1− x)) because Memristors have the capacity of storing the resistance a (see page 45 the Memristor; and see page 47) and are configurable and time variant.
While the cut-off frequency of the memristive impedance is an inherent characteristic of the component/circuit (cut-off frequency Fc of memristor filter is found by Fc = 1/ 2ΠMkC, where Mk = ɑRA + (1- ɑ)RB), and Ascoli teaches the selection of the values of the resistances RA and RB of the memristor to obtain a desired cut-off frequency, Wang-Ascoli-Keshmiri still does not explicitly teach wherein the cutoff frequency of the virtual memristive impedance is tuned relative to the switching frequency of the power converter such that the virtual memristive low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter.
However, Price teaches a voltage converter comprising an impedance or low pass filter (see Col 6 line 62-63 “the HF filter 412 may be a first order low-pass filter), wherein the cutoff frequency of the impedance is tuned relative to a switching frequency of the power converter such that the low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter (interpreted in the BRI in light of the disclosure as “less than a switching frequency of the converter”; see Price Col 7 line 1-10 “…the cutoff frequency (e.g., the −3 dB frequency) for the HF filter 412 may be set below the switching frequency of the DC/DC converter 100, …For example, with a converter switching frequency of 140 MHz and a 0 dB crossover frequency for the error amplifier 410 of 1.7 MHz, a filter frequency of 25 MHz may be used to suppress frequencies of signal components that would otherwise sneak through the error amplifier 410 and allow the individual phase drive signals to be generated with the desired phase shifts” ; also, see Col 10 Claim 11).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang-Ascoli- Keshmiri’s combination as taught above to include wherein the cutoff frequency of the impedance is tuned relative to a switching frequency of the power converter such that the low pass filter suppresses switching noise of the power converter while maintaining frequencies relating to transient responses of the power converter as taught by Price in order to reduce or suppress frequencies found in the output signal and also to reduce the output ripple voltage which reduces the amplitude of the HF output ripple and may allow for automatic phase current balancing to take place (see Col 7 lines 1-15) and apply the teachings of Price such as setting the cut-frequency of the impedance at a value less than the switching frequency of the converter in the combination of Wang-Ascoli-Keshmiri including the virtual memristive impedance to set the cut-off frequency of their combination’s Memristive impedance relative or less than a switching frequency of the power converter to reduce the output ripple voltage which reduces the amplitude of the HF output ripple and may allow for automatic phase current balancing to take place as suggested by Price (see Col 7 lines 1-15).
Wang teaches that the virtual impedances are controllers (see 7020 Col 1 par. 1 “virtual impedance controllers and their implementation issues…”). However, Wang-Ascoli-Keshmiri-Price does not explicitly teach one or more processors operable to execute a set of computer-executable instructions; and memory operable to store the set of computer-executable instructions operable to: perform the functions of claim 8.
However, Hartman teaches a system comprising one or more processors operable to execute a set of computer-executable instructions; and memory operable to store the set of computer-executable instructions operable to: implementing function of a power converter and virtual impedance (see [0050] “The digital measurements of output voltage and current are provided to a processor which implements the control function of one of the previously described controllers 20, 30, 80. The processor in turn provides a control signal to an output circuit or driver 85 which in turn provides a control signal output to a PWM or other modulator circuit. In some arrangements, the PWM or other modulator circuit may also be provided within the integrated circuit 90).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Wang’s combination as taught above to include one or more processors operable to execute a set of computer-executable instructions; and memory operable to store the set of computer-executable instructions operable to: implementing functions of a power converter and virtual impedance of Wang-Ascoli-Keshmiri-Price as taught by Hartman in order to provide a computer implemented method implementing the functions of claim 1 (see [0050-0053]) and to reconfigure the components of the system (see [0053]).
As to claim 10, this claim is the system claim corresponding to the method claim 3 and is rejected for the same reasons mutatis mutandis.
As to claim 11, this claim is the system claim corresponding to the method claim 4 and is rejected for the same reasons mutatis mutandis.
As to claim 12, this claim is the system claim corresponding to the method claim 5 and is rejected for the same reasons mutatis mutandis.
As to claim 13, this claim is the system claim corresponding to the method claim 6 and is rejected for the same reasons mutatis mutandis.
As to claim 14, this claim is the system claim corresponding to the method claim 7 and is rejected for the same reasons mutatis mutandis.
As to claim 15, this claim is a non-transitory computer readable medium claim corresponding to the method claim 8 and is rejected for the same reasons mutatis mutandis.
As to claim 17, this claim is a non-transitory computer readable medium claim corresponding to the method claim 3 and is rejected for the same reasons mutatis mutandis.
As to claim 18, this claim is a non-transitory computer readable medium claim corresponding to the method claim 4 and is rejected for the same reasons mutatis mutandis.
As to claim 19, this claim is a non-transitory computer readable medium claim corresponding to the method claim 5 and is rejected for the same reasons mutatis mutandis.
As to claim 20, this claim is a non-transitory computer readable medium claim corresponding to the method claim 6 and is rejected for the same reasons mutatis mutandis.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLVIN LOPEZ ALVAREZ whose telephone number is (571) 270-7686 and fax (571) 270-8686. The examiner can normally be reached Monday thru Friday from 9:00 A.M. to 6:00 P.M.
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/O. L./
Examiner, Art Unit 2117
/DARRIN D DUNN/Patent Examiner, Art Unit 2117
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