Experimental study of event based PID controllers with different sampling strategies. Application to brushless DC motor networked control system

2015 ◽  
Author(s):  
Julio Ariel Romero ◽  
Roberto Sanchis ◽  
Elena Arrebola
Keyword(s):  
Experimental Study ◽  
Control System ◽  
Dc Motor ◽  
Networked Control System ◽  
Networked Control ◽  
Pid Controllers ◽  
Brushless Dc Motor ◽  
Sampling Strategies ◽  
Brushless Dc ◽  
Event Based

Designed Controller of Permanent Magnet Brushless DC Motor Based on DSP

2014 ◽  
Vol 672-674 ◽  
pp. 1210-1213 ◽  
Author(s):  
Gui Yin Zhan
Keyword(s):  
Control System ◽  
Permanent Magnet ◽  
Digital Signal Processor ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Development Environment ◽  
Brushless Dc ◽  
Detection Circuit ◽  
Software Program ◽  
Permanent Magnet Brushless Dc

A design scheme of the control system was put forward to solve the performance control problems of the motor in this paper, combining with the composition and working principle of permanent magnet brushless DC motor. Hardware circuit of the control system was designed with digital signal processor (DSP) as the core, which mainly consists of the power drive circuit, the motor position, speed detection circuit and winding current detection circuit. Software flow of the control system was also designed, and software program debugging was achieved on CCS3.3 DSP integrated development environment, and the rationality of the software program was validated.

Design and Implementation of Fuzzy PID Controller for Brushless DC Motor Control System

2013 ◽  
Vol 432 ◽  
pp. 472-477
Author(s):  
Wei Fan ◽  
Tao Chen
Keyword(s):  
Control System ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Fuzzy Pid ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

This paper presents a robust fuzzy proportional-integral-derivative (PID) controller for brushless DC motor (BLDCM) control system. The hardware circuit of the BLDCM control system is designed and implemented using a digital signal processor (DSP) TMS320LF2407A and a monolithic BLDCM controller MC33035 as the core. Furthermore, a fuzzy PID controller, which combines the advantages of good robustness of fuzzy controller and high precision of conventional PID controller, is employed in the hardware system, thereby yielding a digital, intelligent BLDCM control system. Experimental results have shown that the control system can run steadily and control accurately, and have convincingly demonstrated the usefulness of the proposed fuzzy PID controller in BLDCM control system.

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