Application of fuzzy PID control in PMLSM servo drive system

2015 ◽  
Author(s):  
Juan Wang ◽  
Di Li
Keyword(s):  
Pid Control ◽  
Drive System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Servo Drive ◽  
Servo Drive System

scholarly journals Design and Analysis of a Drive System for a Series Manipulator Based on Orthogonal-Fuzzy PID Control

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1051 ◽  
Author(s):  
Zhou ◽  
Chen ◽  
Zhou ◽  
Liu
Keyword(s):  
Motion Control ◽  
Pid Control ◽  
Control Method ◽  
Simulation Analysis ◽  
Drive System ◽  
Test Method ◽  
Fuzzy Pid ◽  
Control Effect ◽  
Fuzzy Pid Control ◽  
Orthogonal Test Method

Because the proportional–integral–derivative (PID) parameters selected by experience are random, the control effect of fuzzy PID cannot be optimized. In order to improve the accuracy and stability of robot motion control, an orthogonal-fuzzy PID intelligent control method is proposed. In this paper, the electric steering gear is used as the actuator, and the mathematical model of the servo motor joint drive system is established. The simulation analysis of the original control, PID control, fuzzy PID control, and orthogonal-fuzzy PID control of the manipulator joints in the Simulink software simulation environment and the motion control experiment of the manipulator show that using the orthogonal test method to adjust the PID parameters can quickly determine the appropriate PID parameters and greatly reduce the number of trials. The rise time, adjustment time, and overshoot of the system are significantly reduced by using fuzzy PID control, which can improve the adaptability of the system. By comparing and analyzing fuzzy PID and orthogonal-fuzzy PID control methods, it can be found that the system of orthogonal-fuzzy PID for optimal factor level combination (Kp = 0.1, Ki = 30 and Kd = 0.02) is the optimal system. The experiment results show that the orthogonal-fuzzy PID can further improve the accuracy of the system and reduce the oscillation process of the system near the steady state and make the motion more stable.

New Hydraulic Synchronization System Based on Fuzzy PID Control Strategy

2013 ◽  
Vol 819 ◽  
pp. 229-233
Author(s):  
Zhong Liu ◽  
Jia Chen ◽  
Kai Zhang
Keyword(s):  
Control Strategy ◽  
Pid Control ◽  
High Speed ◽  
Drive System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Synchronization System ◽  
Switching Valve ◽  
Synchronous Drive ◽  
High Speed Switching

Proposition of a high-speed switching valve pilot control of two-cylinder two-way electro-hydraulic synchronous drive system, the establishment of a mathematical model of the system, and using fuzzy PID control strategy designed controller, at the same time building a electro-hydraulic synchronization system simulation model based on fuzzy PID controller . Simulation results show that ,when using the fuzzy PID control strategy, slave cylinder of the synchronization system follow the initiative cylinder movement well, the peak-to-average speed of the slave cylinder is 20.3mm / s. Fuzzy PID control process according to the operating conditions change error and error change, by which it has automatic adjustment of PID parameters of the synchronization system. Therefore, fuzzy PID control has better adaptive ability, and the synchronization error is 0.04 mm, achieving high synchronization accuracy. Verifying that high-speed switching valve pilot control of the synchronous drive system and its control strategy is feasible.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

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