Piezoelectric resonators are widely used in frequency reference devices, mass sensors, resonant sensors(such as gyros and accelerometers), etc. Piezoelectric resonators usually work in a special resonant mode. Obtaini...Piezoelectric resonators are widely used in frequency reference devices, mass sensors, resonant sensors(such as gyros and accelerometers), etc. Piezoelectric resonators usually work in a special resonant mode. Obtaining working resonant mode with high quality is key to improve the performance of piezoelectric resonators. In this paper, the resonance characteristics of a rectangular lead zirconium titanate(PZT) piezoelectric resonator are studied. On the basis of the field-programmable gate array(FPGA) embedded system, direct digital synthesizer(DDS) and automatic gain controller(AGC) are used to generate the driving signals with precisely adjustable frequency and amplitude. The driving signals are used to excite the piezoelectric resonator to the working vibration mode. The influence of the connection of driving electrodes and voltage amplitude on the vibration of the resonator is studied. The quality factor and vibration linearity of the resonator are studied with various driving methods mentioned in this paper. The resonator reaches resonant mode at 330 kHz by different driving methods.The relationship between resonant amplitude and driving signal amplitude is linear. The quality factor reaches over 150 by different driving methods. The results provide a theoretical reference for the efficient excitation of the piezoelectric resonator.展开更多
A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchr...A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM,the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy,the time speed measurement algorithm,the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore,the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.展开更多
An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the conv...An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.展开更多
High performance computer is often required by model predictive control(MPC) systems due to the heavy online computation burden.To extend MPC to more application cases with low-cost computation facilities, the impleme...High performance computer is often required by model predictive control(MPC) systems due to the heavy online computation burden.To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array(FPGA) system is studied.For the dynamic matrix control(DMC) algorithm,the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system.The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.展开更多
The Ocean 4A scatterometer, expected to be launched in 2024, is poised to be the world’s first spaceborne microwave scatterometer utilizing a digital beamforming system. To ensure high-precision measurements and perf...The Ocean 4A scatterometer, expected to be launched in 2024, is poised to be the world’s first spaceborne microwave scatterometer utilizing a digital beamforming system. To ensure high-precision measurements and performance sta-bility across diverse environments, stringent requirements are placed on the dynamic range of its receiving system. This paper provides a detailed exposition of a field-programmable gate array (FPGA)-based automatic gain control (AGC) design for the spaceborne scatterometer. Implemented on an FPGA, the algo-rithm harnesses its parallel processing capabilities and high-speed performance to monitor the received echo signals in real time. Employing an adaptive AGC algorithm, the system gene-rates gain control codes applicable to the intermediate fre-quency variable attenuator, enabling rapid and stable adjust-ment of signal amplitudes from the intermediate frequency amplifier to an optimal range. By adopting a purely digital pro-cessing approach, experimental results demonstrate that the AGC algorithm exhibits several advantages, including fast con-vergence, strong flexibility, high precision, and outstanding sta-bility. This innovative design lays a solid foundation for the high-precision measurements of the Ocean 4A scatterometer, with potential implications for the future of spaceborne microwave scatterometers.展开更多
In order to improve the bias stability of the micro-electro mechanical system（MEMS） gyroscope and reduce the impact on the bias from environmental temperature,a digital signal processing method is described for impr...In order to improve the bias stability of the micro-electro mechanical system（MEMS） gyroscope and reduce the impact on the bias from environmental temperature,a digital signal processing method is described for improving the accuracy of the drive phase in the gyroscope drive mode.Through the principle of bias signal generation,it can be concluded that the deviation of the drive phase is the main factor affecting the bias stability.To fulfill the purpose of precise drive phase control,a digital signal processing circuit based on the field-programmable gate array（FPGA） with the phase-lock closed-loop control method is described and a demodulation method for phase error suppression is given.Compared with the analog circuit,the bias drift is largely reduced in the new digital circuit and the bias stability is improved from 60 to 19 °/h.The new digital control method can greatly increase the drive phase accuracy,and thus improve the bias stability.展开更多
In a conventional direct torque control(CDTC) of the induction motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods a...In a conventional direct torque control(CDTC) of the induction motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods are used in the literature. Nevertheless,these methods increase the algorithm complexity and dependency on the machine parameters such as the space vector modulation(SVM). The fuzzy logic control method is utilized in this work to decrease these ripples. Moreover, to eliminate the mechanical sensor the extended kalman filter(EKF) is used, in order to reduce the cost of the system and the rate of maintenance. Furthermore, in the domain of controlling the real-time induction motor drives, two principal digital devices are used such as the hardware(FPGA) and the digital signal processing(DSP). The latter is a software solution featured by a sequential processing that increases the execution time. However, the FPGA is featured by a high processing speed because of its parallel processing. Therefore, using the FPGA it is possible to implement complex algorithms with low execution time and to enhance the control bandwidth. The large bandwidth is the key issue to increase the system performances. This paper presents the interest of utilizing the FPGAs to implement complex control algorithms of electrical systems in real time. The suggested sensorless direct torque control using the fuzzy logic(DTFC) of an induction motor is successfully designed and implemented on an FPGA Virtex 5 using xilinx system generator. The simulation and implementation results show proposed approach s performances in terms of ripples, stator current harmonic waves, execution time, and short design time.展开更多
Combing with the generalized Hamiltonian system theory,by introducing a special form of sinusoidal function,a class of n-dimensional(n=1,2,3)controllable multi-scroll conservative chaos with complicated dynamics is co...Combing with the generalized Hamiltonian system theory,by introducing a special form of sinusoidal function,a class of n-dimensional(n=1,2,3)controllable multi-scroll conservative chaos with complicated dynamics is constructed.The dynamics characteristics including bifurcation behavior and coexistence of the system are analyzed in detail,the latter reveals abundant coexisting flows.Furthermore,the proposed system passes the NIST tests and has been implemented physically by FPGA.Compared to the multi-scroll dissipative chaos,the experimental portraits of the proposed system show better ergodicity,which have potential application value in secure communication and image encryption.展开更多
Afuzzy controller based oni mproved Generalized-Membership-Function(GMF) algorithmfor afuel cell generationsys-tem wasintroduced.Under the demands on control in application of the converter,a Field Programmable Gate A...Afuzzy controller based oni mproved Generalized-Membership-Function(GMF) algorithmfor afuel cell generationsys-tem wasintroduced.Under the demands on control in application of the converter,a Field Programmable Gate Array(FPGA) re-alization method to manage the power flow was given.This control systembased onthe proposed modified GMF was proved to bea universal approxi mation systemin theory.The fuzzy control technique was combined with Eletronic Design Automatic(EDA)technique and a paralleling fuzzy controller was i mplemented in FPGA.Paralleling fuzzy controller based oni mproved GMF algo-rithm wasi mplemented on a Cyclone FPGA.The result of si mulation based on QuartusII confirmed the validity of the proposed method.展开更多
Electron cyclotron resonance heating (ECRH) system is one of the most important Tokamak auxiliary heating methods. However, there are growing demands for ECRH system as the physical experiments progress which meanwhil...Electron cyclotron resonance heating (ECRH) system is one of the most important Tokamak auxiliary heating methods. However, there are growing demands for ECRH system as the physical experiments progress which meanwhile adds the difficulty of designing and building the control system of its power source. In this paper, the method of designing a control system based on Single Chip Microcomputer (SCM) and Field Programmable Gate Array (FPGA) is introduced according to its main requirements. The experimental results show that the control system in this paper achieves the conversion of different working modes, gets exact timing, and realizes the failure protection in 10us thus can be used in the ECRH system.展开更多
In modern manufacturing equipment control area,controller is required to deliver higher computing capability for adopting advanced algorithms to meet speed and accuracy requirements,and reconfigurabilities for changin...In modern manufacturing equipment control area,controller is required to deliver higher computing capability for adopting advanced algorithms to meet speed and accuracy requirements,and reconfigurabilities for changing or(and)adding features or functions.This paper presents a methodology in design and implementation of a high performance and reconfigurable platform for manufacturing equipment control.This methodology is in virtue of system on a programmable chip(SoPC)technolo- gy but replacing the on-chip processor by an external high performance,floating-point digital signal processor(DSP).The appli- cation of the DSP is designed as a multi-threaded framework,which has more flexibilities than a traditional single-loop one.Fur- thermore,the field programmable gate array(FPGA)system can be reconfigured easily and quickly to meet a new requirement by dragging and dropping pre-built components in a SoPC building environment.As a result,the controller platform is more recon- figurable in terms of algorithms and functions.This platform is implemented in a 3-axis milling machine control and the result indicates that the design and implementation presented in this paper is feasible.展开更多
Neuromorphic computing is considered to be the future of machine learning,and it provides a new way of cognitive computing.Inspired by the excellent performance of spiking neural networks(SNNs)on the fields of low-pow...Neuromorphic computing is considered to be the future of machine learning,and it provides a new way of cognitive computing.Inspired by the excellent performance of spiking neural networks(SNNs)on the fields of low-power consumption and parallel computing,many groups tried to simulate the SNN with the hardware platform.However,the efficiency of training SNNs with neuromorphic algorithms is not ideal enough.Facing this,Michael et al.proposed a method which can solve the problem with the help of DNN(deep neural network).With this method,we can easily convert a well-trained DNN into an SCNN(spiking convolutional neural network).So far,there is a little of work focusing on the hardware accelerating of SCNN.The motivation of this paper is to design an SNN processor to accelerate SNN inference for SNNs obtained by this DNN-to-SNN method.We propose SIES(Spiking Neural Network Inference Engine for SCNN Accelerating).It uses a systolic array to accomplish the task of membrane potential increments computation.It integrates an optional hardware module of max-pooling to reduce additional data moving between the host and the SIES.We also design a hardware data setup mechanism for the convolutional layer on the SIES with which we can minimize the time of input spikes preparing.We implement the SIES on FPGA XCVU440.The number of neurons it supports is up to 4000 while the synapses are 256000.The SIES can run with the working frequency of 200 MHz,and its peak performance is 1.5625 TOPS.展开更多
Emerging applications widely use field-programmable gate array(FPGA)prototypes as a tool to verify modern very-large-scale integration(VLSI)circuits,imposing many problems,including routing failure caused by the limit...Emerging applications widely use field-programmable gate array(FPGA)prototypes as a tool to verify modern very-large-scale integration(VLSI)circuits,imposing many problems,including routing failure caused by the limited number of connections among blocks of FPGAs therein.Such a shortage of connections can be alleviated through time-division multiplexing(TDM),by which multiple signals sharing an identical routing channel can be transmitted.In this context,the routing quality dominantly decides the performance of such systems,proposing the requirement of minimizing the signal delay between FPGA pairs.This paper proposes algorithms for the routing problem in a multi-FPGA system with TDM support,aiming to minimize the maximum TDM ratio.The algorithm consists of two major stages:(1)A method is proposed to set the weight of an edge according to how many times it is shared by the routing requirements and consequently to compute a set of approximate minimum Steiner trees.(2)A ratio assignment method based on the edge-demand framework is devised for assigning ratios to the edges respecting the TDM ratio constraints.Experiments were conducted against the public benchmarks to evaluate our proposed approach as compared with all published works,and the results manifest that our method achieves a better TDM ratio in comparison.展开更多
The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learn...The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learning controller for a real application and reduce the memory size for implementation, a current error based sampled-data proportional-derivative(PD) type iterative learning controller is proposed for control systems with initial resetting error, input disturbance and output measurement noise in this paper.The proposed iterative learning controller is simple and effective. The first contribution in this paper is to prove the learning error convergence via a rigorous technical analysis. It is shown that the learning error will converge to a residual set if a forgetting factor is introduced in the controller. All the theoretical results are also shown by computer simulations. The second main contribution is to realize the iterative learning controller by a digital circuit using a field programmable gate array(FPGA) chip applied to repetitive position tracking control of direct current(DC) motors. The feasibility and effectiveness of the proposed current error based sampleddata iterative learning controller are demonstrated by the experiment results. Finally, the relationship between learning performance and design parameters are also discussed extensively.展开更多
Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we p...Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.展开更多
Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This cont...Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This control method, in contrast with voltage control, provides good dynamics, good stability and implicit over current protection. However, the most important concern of digital implementation of HCC is related with the sampling period of the measured currents. This paper presents a predictive hysteresis current control (HCC) for grid connected voltage source inverter and its FPGA implementation. Simulation and experimental results are provided to verify the validity of the proposed implementation.展开更多
Referring to the shortages that the process of traditional greenhouse measurement by using thermometer and hygrometer is complex,the measurement result is not accurate,and the control system operation is cumbersome,a ...Referring to the shortages that the process of traditional greenhouse measurement by using thermometer and hygrometer is complex,the measurement result is not accurate,and the control system operation is cumbersome,a greenhouse temperature and humidity(TH)control system based on CC3200 is designed.The system uses FPGA as the main controller,sends the TH signals to the wireless module CC3200 by controlling DHT22.The proposed system realizes the remote transmission of data and the automatic control of system.展开更多
With the continuous evolution of electronic technology,field-programmable gate array(FPGA)has demonstrated significant advantages in the realm of signal acquisition and processing,and signal acquisition plays a pivota...With the continuous evolution of electronic technology,field-programmable gate array(FPGA)has demonstrated significant advantages in the realm of signal acquisition and processing,and signal acquisition plays a pivotal role in the practical applications of laser gyros.By analysis of the output signals from a laser gyro and an accelerometer,this paper presents a circuit design for signal acquisition of the laser gyro based on domestic devices.The design incorporates a finite impulse response(FIR)filter to process the gyro signal and employs a small-volume,impact-resistant quartz flexible accelerometer for signal aquisition.Simulation results demonstrate that the errors in X,Y,and Z axes fall within acceptable ranges while meeting filtering requirements.The use of FPGA for signal acquisition and preprocessing enhances configuration flexibility,which provides an idea and method for optimizing performance and processing signals in laser gyro applications.展开更多
Integrated optoelectronic chips working in the visible spectrum range have promising applications in augmented reality and virtual reality,quantum information processing,biosensors,and more.A silicon nitride optical p...Integrated optoelectronic chips working in the visible spectrum range have promising applications in augmented reality and virtual reality,quantum information processing,biosensors,and more.A silicon nitride optical phased array(OPA)can shape and steer light to enable these applications on a compact chip without moving parts.However,smaller wavelength,waveguide size,and the thermo-optic coefficient pose challenges in processing,calibration,and control of silicon nitride OPA chips.In this work,a high-speed phase control system for 532 nm silicon nitride OPA,utilizing a field programmable gate array and a digital-to-analog converter,achieves a 7.4μs voltage configuration.With this system,the single-shot multivoltage optimization of beam calibration of the OPA for tens of milliseconds is realized,and the beam scanning in the range of ±24° is demonstrated.The system fully meets the needs of high-speed scanning of silicon nitride OPA,advancing OPA's development and applications.展开更多
文摘Piezoelectric resonators are widely used in frequency reference devices, mass sensors, resonant sensors(such as gyros and accelerometers), etc. Piezoelectric resonators usually work in a special resonant mode. Obtaining working resonant mode with high quality is key to improve the performance of piezoelectric resonators. In this paper, the resonance characteristics of a rectangular lead zirconium titanate(PZT) piezoelectric resonator are studied. On the basis of the field-programmable gate array(FPGA) embedded system, direct digital synthesizer(DDS) and automatic gain controller(AGC) are used to generate the driving signals with precisely adjustable frequency and amplitude. The driving signals are used to excite the piezoelectric resonator to the working vibration mode. The influence of the connection of driving electrodes and voltage amplitude on the vibration of the resonator is studied. The quality factor and vibration linearity of the resonator are studied with various driving methods mentioned in this paper. The resonator reaches resonant mode at 330 kHz by different driving methods.The relationship between resonant amplitude and driving signal amplitude is linear. The quality factor reaches over 150 by different driving methods. The results provide a theoretical reference for the efficient excitation of the piezoelectric resonator.
基金the Natural Science Foundation of Hubei Province (No.2005ABA301)
文摘A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM,the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy,the time speed measurement algorithm,the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore,the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.
文摘An intelligent fuzzy logic inference pipeline for the control of a dc-dc buck-boost converter was designed and built using a semi-custom VLSI chip. The fuzzy linguistics describing the switching topologies of the converter was mapped into a look-up table that was synthesized into a set of Boolean equations. A VLSI chip–a field programmable gate array (FPGA) was used to implement the Boolean equations. Features include the size of RAM chip independent of number of rules in the knowledge base, on-chip fuzzification and defuzzification, faster response with speeds over giga fuzzy logic inferences per sec (FLIPS), and an inexpensive VLSI chip. The key application areas are: 1) on-chip integrated controllers;and 2) on-chip co-integration for entire system of sensors, circuits, controllers, and detectors for building complete instrument systems.
基金the National Science Foundation of China(Nos.60934007 and 61074060)the Postdoctoral Science Foundation of China(No.20090460627)+2 种基金the Postdoctoral Scientific Program of Shanghai (No.10R21414600)the Specialized Research Fund for the Doctoral Program of Higher Education (No.20070248004)the China Postdoctoral Science Foundation Special Support(No.201003272)
文摘High performance computer is often required by model predictive control(MPC) systems due to the heavy online computation burden.To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array(FPGA) system is studied.For the dynamic matrix control(DMC) algorithm,the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system.The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.
文摘The Ocean 4A scatterometer, expected to be launched in 2024, is poised to be the world’s first spaceborne microwave scatterometer utilizing a digital beamforming system. To ensure high-precision measurements and performance sta-bility across diverse environments, stringent requirements are placed on the dynamic range of its receiving system. This paper provides a detailed exposition of a field-programmable gate array (FPGA)-based automatic gain control (AGC) design for the spaceborne scatterometer. Implemented on an FPGA, the algo-rithm harnesses its parallel processing capabilities and high-speed performance to monitor the received echo signals in real time. Employing an adaptive AGC algorithm, the system gene-rates gain control codes applicable to the intermediate fre-quency variable attenuator, enabling rapid and stable adjust-ment of signal amplitudes from the intermediate frequency amplifier to an optimal range. By adopting a purely digital pro-cessing approach, experimental results demonstrate that the AGC algorithm exhibits several advantages, including fast con-vergence, strong flexibility, high precision, and outstanding sta-bility. This innovative design lays a solid foundation for the high-precision measurements of the Ocean 4A scatterometer, with potential implications for the future of spaceborne microwave scatterometers.
基金The National Natural Science Foundation of China (No.60974116)the Research Fund of Aeronautics Science (No. 20090869007)Specialized Research Fund for the Doctoral Program of Higher Education(No. 200802861063)
文摘In order to improve the bias stability of the micro-electro mechanical system（MEMS） gyroscope and reduce the impact on the bias from environmental temperature,a digital signal processing method is described for improving the accuracy of the drive phase in the gyroscope drive mode.Through the principle of bias signal generation,it can be concluded that the deviation of the drive phase is the main factor affecting the bias stability.To fulfill the purpose of precise drive phase control,a digital signal processing circuit based on the field-programmable gate array（FPGA） with the phase-lock closed-loop control method is described and a demodulation method for phase error suppression is given.Compared with the analog circuit,the bias drift is largely reduced in the new digital circuit and the bias stability is improved from 60 to 19 °/h.The new digital control method can greatly increase the drive phase accuracy,and thus improve the bias stability.
文摘In a conventional direct torque control(CDTC) of the induction motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods are used in the literature. Nevertheless,these methods increase the algorithm complexity and dependency on the machine parameters such as the space vector modulation(SVM). The fuzzy logic control method is utilized in this work to decrease these ripples. Moreover, to eliminate the mechanical sensor the extended kalman filter(EKF) is used, in order to reduce the cost of the system and the rate of maintenance. Furthermore, in the domain of controlling the real-time induction motor drives, two principal digital devices are used such as the hardware(FPGA) and the digital signal processing(DSP). The latter is a software solution featured by a sequential processing that increases the execution time. However, the FPGA is featured by a high processing speed because of its parallel processing. Therefore, using the FPGA it is possible to implement complex algorithms with low execution time and to enhance the control bandwidth. The large bandwidth is the key issue to increase the system performances. This paper presents the interest of utilizing the FPGAs to implement complex control algorithms of electrical systems in real time. The suggested sensorless direct torque control using the fuzzy logic(DTFC) of an induction motor is successfully designed and implemented on an FPGA Virtex 5 using xilinx system generator. The simulation and implementation results show proposed approach s performances in terms of ripples, stator current harmonic waves, execution time, and short design time.
基金Project supported by the Natural Science Foundation of Tianjin,China(Grant No.18JCYBJC87700)the Natural Science Foundation of China(Grant No.61603274)。
文摘Combing with the generalized Hamiltonian system theory,by introducing a special form of sinusoidal function,a class of n-dimensional(n=1,2,3)controllable multi-scroll conservative chaos with complicated dynamics is constructed.The dynamics characteristics including bifurcation behavior and coexistence of the system are analyzed in detail,the latter reveals abundant coexisting flows.Furthermore,the proposed system passes the NIST tests and has been implemented physically by FPGA.Compared to the multi-scroll dissipative chaos,the experimental portraits of the proposed system show better ergodicity,which have potential application value in secure communication and image encryption.
文摘Afuzzy controller based oni mproved Generalized-Membership-Function(GMF) algorithmfor afuel cell generationsys-tem wasintroduced.Under the demands on control in application of the converter,a Field Programmable Gate Array(FPGA) re-alization method to manage the power flow was given.This control systembased onthe proposed modified GMF was proved to bea universal approxi mation systemin theory.The fuzzy control technique was combined with Eletronic Design Automatic(EDA)technique and a paralleling fuzzy controller was i mplemented in FPGA.Paralleling fuzzy controller based oni mproved GMF algo-rithm wasi mplemented on a Cyclone FPGA.The result of si mulation based on QuartusII confirmed the validity of the proposed method.
文摘Electron cyclotron resonance heating (ECRH) system is one of the most important Tokamak auxiliary heating methods. However, there are growing demands for ECRH system as the physical experiments progress which meanwhile adds the difficulty of designing and building the control system of its power source. In this paper, the method of designing a control system based on Single Chip Microcomputer (SCM) and Field Programmable Gate Array (FPGA) is introduced according to its main requirements. The experimental results show that the control system in this paper achieves the conversion of different working modes, gets exact timing, and realizes the failure protection in 10us thus can be used in the ECRH system.
基金Supported by the Foundation:Guangdong Provincial Science and Technology Committee under Grant No.2002C1020407.
文摘In modern manufacturing equipment control area,controller is required to deliver higher computing capability for adopting advanced algorithms to meet speed and accuracy requirements,and reconfigurabilities for changing or(and)adding features or functions.This paper presents a methodology in design and implementation of a high performance and reconfigurable platform for manufacturing equipment control.This methodology is in virtue of system on a programmable chip(SoPC)technolo- gy but replacing the on-chip processor by an external high performance,floating-point digital signal processor(DSP).The appli- cation of the DSP is designed as a multi-threaded framework,which has more flexibilities than a traditional single-loop one.Fur- thermore,the field programmable gate array(FPGA)system can be reconfigured easily and quickly to meet a new requirement by dragging and dropping pre-built components in a SoPC building environment.As a result,the controller platform is more recon- figurable in terms of algorithms and functions.This platform is implemented in a 3-axis milling machine control and the result indicates that the design and implementation presented in this paper is feasible.
基金The work was supported by the HeGaoJi Program of China under Grant Nos.2017ZX01028103-002 and 2017ZX01038104-002the National Natural Science Foundation of China under Grant No.61472432.
文摘Neuromorphic computing is considered to be the future of machine learning,and it provides a new way of cognitive computing.Inspired by the excellent performance of spiking neural networks(SNNs)on the fields of low-power consumption and parallel computing,many groups tried to simulate the SNN with the hardware platform.However,the efficiency of training SNNs with neuromorphic algorithms is not ideal enough.Facing this,Michael et al.proposed a method which can solve the problem with the help of DNN(deep neural network).With this method,we can easily convert a well-trained DNN into an SCNN(spiking convolutional neural network).So far,there is a little of work focusing on the hardware accelerating of SCNN.The motivation of this paper is to design an SNN processor to accelerate SNN inference for SNNs obtained by this DNN-to-SNN method.We propose SIES(Spiking Neural Network Inference Engine for SCNN Accelerating).It uses a systolic array to accomplish the task of membrane potential increments computation.It integrates an optional hardware module of max-pooling to reduce additional data moving between the host and the SIES.We also design a hardware data setup mechanism for the convolutional layer on the SIES with which we can minimize the time of input spikes preparing.We implement the SIES on FPGA XCVU440.The number of neurons it supports is up to 4000 while the synapses are 256000.The SIES can run with the working frequency of 200 MHz,and its peak performance is 1.5625 TOPS.
基金supported by the Natural Science Foundation of Fujian Province(No.2020J01845)the National Natural Science Foundation of China(Nos.61772005 and 11871280)+1 种基金the Outstanding Youth Innovation Team Project for Universities of Shandong Province(No.2020KJN008)Qinglan Project.
文摘Emerging applications widely use field-programmable gate array(FPGA)prototypes as a tool to verify modern very-large-scale integration(VLSI)circuits,imposing many problems,including routing failure caused by the limited number of connections among blocks of FPGAs therein.Such a shortage of connections can be alleviated through time-division multiplexing(TDM),by which multiple signals sharing an identical routing channel can be transmitted.In this context,the routing quality dominantly decides the performance of such systems,proposing the requirement of minimizing the signal delay between FPGA pairs.This paper proposes algorithms for the routing problem in a multi-FPGA system with TDM support,aiming to minimize the maximum TDM ratio.The algorithm consists of two major stages:(1)A method is proposed to set the weight of an edge according to how many times it is shared by the routing requirements and consequently to compute a set of approximate minimum Steiner trees.(2)A ratio assignment method based on the edge-demand framework is devised for assigning ratios to the edges respecting the TDM ratio constraints.Experiments were conducted against the public benchmarks to evaluate our proposed approach as compared with all published works,and the results manifest that our method achieves a better TDM ratio in comparison.
基金supported by National Science Council,Taiwan,China(No.NSC102-2221-E-211-011)National Nature Science Foundation of China(No.61374102)
文摘The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learning controller for a real application and reduce the memory size for implementation, a current error based sampled-data proportional-derivative(PD) type iterative learning controller is proposed for control systems with initial resetting error, input disturbance and output measurement noise in this paper.The proposed iterative learning controller is simple and effective. The first contribution in this paper is to prove the learning error convergence via a rigorous technical analysis. It is shown that the learning error will converge to a residual set if a forgetting factor is introduced in the controller. All the theoretical results are also shown by computer simulations. The second main contribution is to realize the iterative learning controller by a digital circuit using a field programmable gate array(FPGA) chip applied to repetitive position tracking control of direct current(DC) motors. The feasibility and effectiveness of the proposed current error based sampleddata iterative learning controller are demonstrated by the experiment results. Finally, the relationship between learning performance and design parameters are also discussed extensively.
基金supported by the DOE-MMICS SEA-CROGS DE-SC0023191 and the AFOSR MURI FA9550-20-1-0358supported by the SMART Scholarship,which is funded by the USD/R&E(The Under Secretary of Defense-Research and Engineering),National Defense Education Program(NDEP)/BA-1,Basic Research.
文摘Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.
文摘Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This control method, in contrast with voltage control, provides good dynamics, good stability and implicit over current protection. However, the most important concern of digital implementation of HCC is related with the sampling period of the measured currents. This paper presents a predictive hysteresis current control (HCC) for grid connected voltage source inverter and its FPGA implementation. Simulation and experimental results are provided to verify the validity of the proposed implementation.
文摘Referring to the shortages that the process of traditional greenhouse measurement by using thermometer and hygrometer is complex,the measurement result is not accurate,and the control system operation is cumbersome,a greenhouse temperature and humidity(TH)control system based on CC3200 is designed.The system uses FPGA as the main controller,sends the TH signals to the wireless module CC3200 by controlling DHT22.The proposed system realizes the remote transmission of data and the automatic control of system.
文摘With the continuous evolution of electronic technology,field-programmable gate array(FPGA)has demonstrated significant advantages in the realm of signal acquisition and processing,and signal acquisition plays a pivotal role in the practical applications of laser gyros.By analysis of the output signals from a laser gyro and an accelerometer,this paper presents a circuit design for signal acquisition of the laser gyro based on domestic devices.The design incorporates a finite impulse response(FIR)filter to process the gyro signal and employs a small-volume,impact-resistant quartz flexible accelerometer for signal aquisition.Simulation results demonstrate that the errors in X,Y,and Z axes fall within acceptable ranges while meeting filtering requirements.The use of FPGA for signal acquisition and preprocessing enhances configuration flexibility,which provides an idea and method for optimizing performance and processing signals in laser gyro applications.
基金supported by the National Natural Science Foundation of China(Nos.62335019 and 61975243)。
文摘Integrated optoelectronic chips working in the visible spectrum range have promising applications in augmented reality and virtual reality,quantum information processing,biosensors,and more.A silicon nitride optical phased array(OPA)can shape and steer light to enable these applications on a compact chip without moving parts.However,smaller wavelength,waveguide size,and the thermo-optic coefficient pose challenges in processing,calibration,and control of silicon nitride OPA chips.In this work,a high-speed phase control system for 532 nm silicon nitride OPA,utilizing a field programmable gate array and a digital-to-analog converter,achieves a 7.4μs voltage configuration.With this system,the single-shot multivoltage optimization of beam calibration of the OPA for tens of milliseconds is realized,and the beam scanning in the range of ±24° is demonstrated.The system fully meets the needs of high-speed scanning of silicon nitride OPA,advancing OPA's development and applications.
