Design of PMSM Position Servo System Based on Fuzzy Adaptive PI Control

2013 ◽  
Vol 706-708 ◽  
pp. 737-741 ◽  
Author(s):  
Hong Mei Shi ◽  
Zu Jun Yu
Keyword(s):  
Digital Signal Processor ◽  
High Performance ◽  
Permanent Magnet Synchronous Motor ◽  
Servo System ◽  
Experimental System ◽  
Digital Signal ◽  
Adaptive Controller ◽  
Speed Performance ◽  
Position Servo ◽  
Fuzzy Adaptive

A fuzzy adaptive PI controller for permanent magnet synchronous motor (PMSM) position servo system is proposed in this paper. Based on the analysis of PMSM mathematical model, the design of position loop controller is introduced in detail. To verify the effectiveness and accuracy of the fuzzy PI adaptive controller, an experimental system is designed using TMS320F2812 floating-point digital signal processor (DSP) as controller CPU and DR20A as integrated power drive module. The experimental results show that the designed AC position servo system has strong robustness, better speed performance and higher position precision, which can meet the requirements of high performance servo system.

Design of BLDCM Control System with Fuzzy Adaptive Controller

2013 ◽  
Vol 765-767 ◽  
pp. 1791-1795 ◽  
Author(s):  
Zheng Zhong Li ◽  
Li Xia Guo ◽  
Guo Fang Gao
Keyword(s):  
Control System ◽  
Pid Control ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Adaptive Controller ◽  
Dc Motor ◽  
System Structure ◽  
Brushless Dc Motor ◽  
Brushless Dc

To handle the shortages of conventional PID control, recur to the high-performance digital signal processor, combine the fuzzy self-adaption controller with brushless dc motor control system. The results show the control system structure is simplified and the performances of control system are improved comparing to the conventional PID control, the performance index is better than that in conventional PID control system, so the stability of brushless dc motor operation is strengthened.

scholarly journals SHIL and DHIL Simulations of Nonlinear Control Methods Applied for Power Converters Using Embedded Systems

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 241 ◽  
Author(s):  
Arthur Rosa ◽  
Matheus Silva ◽  
Marcos Campos ◽  
Renato Santana ◽  
Welbert Rodrigues ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Nonlinear Control ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Performance ◽  
Power Converters ◽  
Digital Signal ◽  
Simulation Method ◽  
Hardware In The Loop ◽  
Control Techniques

In this work, a new real-time Simulation method is designed for nonlinear control techniques applied to power converters. We propose two different implementations: in the first one (Single Hardware in The Loop: SHIL), both model and control laws are inserted in the same Digital Signal Processor (DSP), and in the second approach (Double Hardware in The Loop: DHIL), the equations are loaded in different embedded systems. With this methodology, linear and nonlinear control techniques can be designed and compared in a quick and cheap real-time realization of the proposed systems, ideal for both students and engineers who are interested in learning and validating converters performance. The methodology can be applied to buck, boost, buck-boost, flyback, SEPIC and 3-phase AC-DC boost converters showing that the new and high performance embedded systems can evaluate distinct nonlinear controllers. The approach is done using matlab-simulink over commodity Texas Instruments Digital Signal Processors (TI-DSPs). The main purpose is to demonstrate the feasibility of proposed real-time implementations without using expensive HIL systems such as Opal-RT and Typhoon-HL.

Sensorless Control of IPMSM Using Modified Current Slope Estimation Method

2012 ◽  
Vol 150 ◽  
pp. 100-104
Author(s):  
Tao Zhang ◽  
Wei Ni ◽  
Hui Ping Zhang ◽  
Sha Sha Wu
Keyword(s):  
Permanent Magnet ◽  
Digital Signal Processor ◽  
Permanent Magnet Synchronous Motor ◽  
Estimation Method ◽  
Digital Signal ◽  
Synchronous Motor ◽  
Low Speed ◽  
Rotor Position ◽  
Operating Region ◽  
Interior Permanent Magnet

When the permanent magnet synchronous motor is operated at a low speed. The rotor position and speed are very difficult to estimate using the extended flux or back EMF method. A novel modified current slope estimating method is used to estimate the rotor position and speed in low speed in this paper. The mathematical models of an interior permanent magnet synchronous motor (IPMSM) are deduced. The basic principle of modified current slope method is introduced. The simulation control system is built based on Matlab and a TMS320LF2407 digital signal processor is used to execute the rotor position and speed estimation. The experimental and simulation results have shown that the rotor position and speed can be accurately estimated in a low-speed operating region.

PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS

2004 ◽  
Vol 12 (02) ◽  
pp. 149-174 ◽  
Author(s):  
KILSEOK CHO ◽  
ALAN D. GEORGE ◽  
RAJ SUBRAMANIYAN ◽  
KEONWOOK KIM
Keyword(s):  
Parallel Algorithms ◽  
Real Time ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Matched Field Processing ◽  
Minimum Variance Distortionless Response ◽  
Distributed Array

Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR–MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR–MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

scholarly journals Optimizing Convolution Neural Network on the TI C6678 multicore DSP

2018 ◽  
Vol 246 ◽  
pp. 03044 ◽  
Author(s):  
Guozhao Zeng ◽  
Xiao Hu ◽  
Yueyue Chen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Deep Learning ◽  
Digital Signal Processor ◽  
High Performance ◽  
Digital Signal ◽  
Automatic Translation ◽  
Convolution Operation ◽  
Multicore Dsp

Convolutional Neural Networks (CNNs) have become the most advanced algorithms for deep learning. They are widely used in image processing, object detection and automatic translation. As the demand for CNNs continues to increase, the platforms on which they are deployed continue to expand. As an excellent low-power, high-performance, embedded solution, Digital Signal Processor (DSP) is used frequently in many key areas. This paper attempts to deploy the CNN to Texas Instruments (TI)’s TMS320C6678 multi-core DSP and optimize the main operations (convolution) to accommodate the DSP structure. The efficiency of the improved convolution operation has increased by tens of times.

Design of Permanent Magnet Synchronous Motor Drive Circuit Based on IPM

2015 ◽  
Vol 743 ◽  
pp. 270-276
Author(s):  
X.L. Lin ◽  
D.F. Dong ◽  
Wei Hu Zhou
Keyword(s):  
Permanent Magnet ◽  
High Performance ◽  
Permanent Magnet Synchronous Motor ◽  
Servo System ◽  
Synchronous Motor ◽  
Power Module ◽  
Fast Tracking ◽  
Drive Circuit ◽  
Intelligent Power Module ◽  
Control System Model

High performance servo system is the basis of fast tracking and precision measurement of laser tracker, and drive circuit is the hardware guarantee of the control algorithm in the system. This paper is concerned with the designed drive circuit of Permanent Magnet Synchronous Motor (PMSM). First, control system model of PMSM is introduced, as well as the PM10CSJ060 Intelligent Power Module (IPM) working principle. Then the drive circuit based on IPM is designed and applied in servo system. Experimental results show that the drive circuit is reliable and stable, with strong anti-interference function, can meet the performance requirements of laser trackers.

Research of Permanent Magnet Synchronous Motor Speed Control System Based on DSP

2012 ◽  
Vol 468-471 ◽  
pp. 2891-2894 ◽  
Author(s):  
Hui Wang ◽  
Xue Ren Dong ◽  
Xiao Wei Yang ◽  
Feng Nan Liu
Keyword(s):  
Control System ◽  
Permanent Magnet ◽  
Digital Signal Processor ◽  
Permanent Magnet Synchronous Motor ◽  
Digital Signal ◽  
Speed Control ◽  
Synchronous Motor ◽  
Motor Speed ◽  
System Solution ◽  
Speed Control System

For requirements Permanent magnet synchronous motor (PMSM) speeds control, the digital signal processor (DSP) is used for speed control system of PMSM. By using space vector pulse width modulation (SVPWM) algorithm, system performance is improved, and system costs are reduced. In this paper, the principle of SVPWM is analyzed, and its implementation is described. Through the analysis of permanent magnet synchronous motor in a different coordinate system in the mathematical model system solution is presented, software design for system is described. A DSP-based PMSM speed control system is build, the system is analyzed in MATLAB simulation. That proves the feasibility of the system.

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