Ying-Shieh Kung

Simulink/Modelsim co-simulation of EKF-based sensorless PMSM drives

Based on Simulink/Modelsim co-simulation technology, the design of EKF (Extended Kalman Filter) for sensorless PMSM (Permanent Magnet Synchronous Motor) drives is presented in this paper. Firstly, a mathematical model for PMSM is derived, the vector control is adopted and the EKF algorithm is introduced. Secondly, the estimation of the rotor flux position and rotor speed based on EKF is applied to sensorless PMSM drives. These estimated values are feed-backed to the current loop of PMSM drive for vector control and to the speed loop of PMSM drive for speed control. Thirdly, the Very-High-Speed IC Hardware Description Language (VHDL) is adopted to describe the behaviour of EKF. Fourthly, the simulation work is performed by MATLAB/Simulink and ModelSim co-simulation mode, provided by Electronic Design Automation (EDA) Simulator Link. The PMSM, inverter and speed command are performed in Simulink and the sensorless speed controller of PMSM drives is executed in ModelSim. Finally, the co-simulation results validate the correctness and effectiveness of the EKF-based sensorless PMSM control system.

Digital hardware implementation of a radial basis function neural network

A high accuracy method to compute the Gaussian function in the radial basis function neural network (RBF NN) is proposed.The computational accuracy of the propose method in the Gaussian function and the overall RBF NN can reach up10-6-10-7.Fast computational ability for a complicated RNF NN is presented by using the digital hardware implementation.Succeed in making the co-simulation environment between Simulink and ModelSim to verify the correctness and the effectiveness of the VHDL (Very high-speed IC Hardware Description Language) code for a 3-5-1 RBF NN.The application of the VHDL code for a 3-5-1 RBF NN to the dynamic identification in the linear system and the PMSM drive system are successfully demonstrated. This work studies a digital hardware implementation of a radial basis function neural network (RBF NN) Firstly, the architecture of the RBF NN, which consists of an input layer, a hidden layer of nonlinear processing neurons with Gaussian function, an output layer and a learning mechanism, is presented. The supervising learning mechanism based on the stochastic gradient descent (SGD) method is applied to update the parameters of RBF NN. Secondly, a very high-speed IC hardware description language (VHDL) is adopted to describe the behavior of the RBF NN. The finite state machine (FSM) is applied for reducing the hardware resource usage. Thirdly, based on the electronic design automation (EDA) simulator link, a co-simulation work by Simulink and ModelSim is applied to verify the VHDL code of RBF NN. Finally, some simulation cases are tested to validate the effectiveness of the proposed digital hardware implementation of the RBF NN. Display Omitted

Field programmable gate array-based servo control integrated chip for a six-axis articulated robot manipulator

The objective of this article is to build a field programmable gate array–based six-axis servo control integrated chip which can integrate the function of a motion trajectory planning and the function of six position/speed/current servo controllers into one integrated chip. In the work, first, a mathematical modeling of a robot manipulator with the actuator using permanent magnet synchronous motor is derived. Second, the proportional controller in the position loop, a proportional–integral controller in the speed loop and a vector controller in the current loop for each axis are applied. Third, a system on a programmable chip) technology which comprises an Altera field programmable gate array chip and an embedded soft-core Nios-II processor is considered to develop the proposed servo control integrated chip. However, in the servo control integrated chip, it has two modules. The first module is an embedded soft-core Nios-II processor which is used to generate the motion trajectory planning by software. The second module presents a six-axis servo controller intellectual property by hardware which is applied to execute six position/speed/current controllers. Therefore, the function of a motion trajectory command and the function of six position/speed/current servo controllers for a six-axis robot manipulator can be integrated into one field programmable gate array. Finally, to verify the effectiveness and correctness of the proposed field programmable gate array–based servo control integrated chip, a six-axis robot manipulator is applied and some experimental results are demonstrated.

Design and Implementation of a Microprocessor-Based PI Controller for PMSM Drives

This work presents a hardware implementation of a simple microprocessor; then uses this microprocessor to design a PI controller for PMSM (Permanent Magnet Synchronous Motor) drives. In this paper, firstly, the mathematical model of PMSM drives is illustrated. Secondly, the architecture of a simple microprocessor based on RTL (Register Transfer Level) method is proposed and the VHDL (Very high speed IC Hardware Description Language) is adopted to describe the behavior of the simple microprocessor. Thirdly, a machine code of PI controller based on the proposed simple microprocessor is designed. Finally, a co-simulation by Simulink/ModelSim is applied and verified the performance of the microprocessor-based PI controller.

FPGA-realization of fuzzy speed controller for PMSM drives without position sensor

This work realizes the speed control for permanent magnet synchronous motor (PMSM) drives under the condition of without position sensor. Rotor flux angle and rotor speed are obtained by using the algorithm of sliding mode observer. And the fuzzy controller is adopted for controlling the speed of PMSM in order to increase the robust performance. In this paper, we provide an approach from modeling, system design, co-simulation in Modelsim/Simulink to experiment in FPGA which can be used to design and validate our proposed control system. Finally, both simulation and experiment results are confirmed the effectiveness and correctness of the proposed FPGA-based fuzzy speed controller for PMSM which is without position sensor.

FPGA Realization of Sensorless PMSM Speed Controller Based on Extended Kalman Filter

Based on extended Kalman filter (EKF), the design and FPGA implementation of a sensorless control intellectual property (IP) for permanent magnet synchronous motor (PMSM) drive are presented in this paper. Firstly, the mathematical model for PMSM is derived and the vector control is built up. Secondly, the rotor flux angle (FA) and rotor speed which are estimated by using EKF are described. These estimated values are feedbacked to the current loop for vector control and to the speed loop for speed control. Thirdly, the very-high-speed IC hardware description language (VHDL) is adopted to describe the behavior of the sensorless speed control IP which includes the circuits of space vector pulse width modulation (SVPWM), coordinate transformation, EKF, and PI controller. Finally, to evaluate the effectiveness and correctness of the proposed of system, a cosimulation work performed by Simulink and ModelSim is firstly conducted. Then, an experimental system by FPGA chip and motor driving board is set up to further validate the performance of the proposed EKF-based sensorless speed control IP.

ModelSim/Simulink Cosimulation and FPGA Realization of a Multiaxis Motion Controller

This paper is to implement a multiaxis servo controller and a motion trajectory planning within one chip. At first, SoPC (system on a programmable chip) technology which is composed of an Altera FPGA (field programmable gate arrays) chip and an embedded soft-core Nios II processor is taken as the development of a multiaxis motion control IC. The multiaxis motion control IC has two modules. The first module is Nios II processor which realizes the motion trajectory planning by software. It includes the step, circular, window, star, and helical motion trajectory. The second module presents a function of the multiaxis position/speed/current controller IP (intellectual property) by hardware. And VHDL (VHSIC Hardware Description Language) is applied to describe the multiaxis servo controller behavior. Before the FPGA realization, a cosimulation work by ModelSim/Simulink is applied to test the VHDL code. Then, this IP combined by Nios II processor will be downloaded to FPGA. Therefore, a fully digital multiaxis motion controller can be realized by a single FPGA chip. Finally, to verify the effectiveness and correctness of the proposed multiaxis motion control IP, a three-axis motion platform (XYZ table) is constructed and some experimental results are presented.

FPGA-Realization of Vector Control for PMSM Drives

The design and implementation of a vector control for Permanent Magnetic Synchronous Motor (PMSM) based on Field Programmable Gate Array (FPGA) technology is presented in this paper. Firstly, a Space Vector Pulse Width Modulation (SVPWM) scheme, vector control method and PI controller are derived. Secondly, the Very-High-Speed IC Hardware Description Language (VHDL) is adopted to describe the behavior of the aforementioned control algorithms. Finally, an experimental system is setup to evaluate the effectiveness and correctness of the proposed vector controller for PMSM drives.