Fuzzy Self-Tuning PID Controller in SEHS

2012 ◽  
Vol 214 ◽  
pp. 765-770
Author(s):  
Lan Sun
Keyword(s):  
Pid Controller ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Fuzzy Pid Controller ◽  
Control Scheme ◽  
Hydraulic Servo ◽  
Self Tuning ◽  
Hybrid Fuzzy Pid ◽  
Better Than

Because of the existing hybrid fuzzy PID controller does not perform, using electric hydraulic servo system application (SEHS). Therefore, when the system parameters change will require a new adjustment of PID controller variable. Therefore, a hybrid fuzzy and fuzzy self-tuning PID control was put forward. With this control scheme was divided into two parts, and the fuzzy controller and fuzzy self-tuning PID controller. Fuzzy controller is used to control the output of the system of the values of the system away from target value. We proved that the performance of the control scheme through the experiment of the motor speed control SEHS. The experimental results show that the proposed a hybrid fuzzy PID controller and fuzzy self-tuning effect is better than that of a hybrid fuzzy and PID controller.

Application of Hybrid Fuzzy PID Control to Auxiliary Workpiece Table

2004 ◽  
Vol 471-472 ◽  
pp. 264-268 ◽  
Author(s):  
Da Wei Zhang ◽  
Yan Ling Tian ◽  
Bing Yan
Keyword(s):  
Pid Controller ◽  
Fuzzy Controller ◽  
Experimental Testing ◽  
Small Range ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Inference Mechanism ◽  
Fuzzy Pid Controller ◽  
Self Tuning ◽  
Hybrid Fuzzy Pid

In order to eliminate the non-linearity of a grinding auxiliary workpiece table, a hybrid fuzzy PID controller has been developed. The two-dimensional fuzzy control with self-tuning factor is utilized to improve the performance. The Max-Min inference mechanism and COG defuzzification method are used to obtain the crisp output of the fuzzy controller. To eliminate the oscillation at balance position, the conventional PID controller is used in the small range of the error and the switch between two controllers can automatically realize according the preset value. Simulation and experimental testing have been carried out to validate the performance of the hybrid fuzzy PID controller.

Single Degree Vibration Platform Self-Tuning Fuzzy PID Controller Design Based on AMESim

2013 ◽  
Vol 310 ◽  
pp. 518-523
Author(s):  
Zhi Qiang Chao ◽  
Xin Ze Li ◽  
Ai Hong Meng
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Simulation Software ◽  
Fuzzy Pid ◽  
Hydraulic Simulation ◽  
Fuzzy Pid Controller ◽  
Single Degree ◽  
Self Tuning

In recent years, hydraulic simulation has become an important means to research hydraulic system, in order to enable the single degree platform vibration curve with better traceability and reach the requirement of the test, this paper represent single degree system platform stimulated by simulation software AMESim, taking the Single degree freedom vibration hydraulic system as an example, MATlab/simulink is applied to the design of the vibration platform system fuzzy PID controller. Through the comparison between the simulation test and traditional PID controller, the designed self-tuning fuzzy controller can control the platform better, with smaller overshoot, faster response, shorter adjusting time, as well as fulfill the permissible accuracy.

Missile Autopilot Design Based on Fuzzy Self-Tuning Immune PID Control

2013 ◽  
Vol 739 ◽  
pp. 550-554 ◽  
Author(s):  
Xu Sheng Gan ◽  
Xue Qin Tang ◽  
Jian Guo Gao
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Variable Parameter ◽  
Feedback Mechanism ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
System A ◽  
Self Tuning ◽  
Better Than

A design of the fuzzy self-tuning immune PID controller is proposed. The controller, which combines immune feedback mechanism and fuzzy PID control, executes the self-tuning of PID parameters in the control system. A simulation experiment is presented in light of a tactical missile autopilot transfer function. Simulation result shows that the performance of fuzzy self-tuning immune PID controller is better than that of fuzzy PID controller, especially in its robust performance for variable parameter system.

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