Design of a self tuning fuzzy PID controller by the accumulated genetic algorithm

2003 ◽  
Author(s):  
Leehter Yao ◽  
Chin-chin Lin
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Self Tuning

scholarly journals Simulation Study of Hydraulic Turbine by Using Self-Tuning Fuzzy PID Controller

2015 ◽  
Vol 3 (1) ◽  
pp. 7-15
Author(s):  
Hakan Açıkgöz ◽  
Ö. Fatih Keçecioğlu ◽  
Mahit Güneş ◽  
Mustafa Şekkeli
Keyword(s):  
Simulation Study ◽  
Pid Controller ◽  
Hydraulic Turbine ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Self Tuning

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.

Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm

2022 ◽  
pp. 014233122110667
Author(s):  
Tufan Dogruer ◽  
Mehmet Serhat Can
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Pid Controller ◽  
Robustness Analysis ◽  
Optimal Solution ◽  
Voltage Regulator ◽  
Fuzzy Pid ◽  
Multi Objective ◽  
Fuzzy Pid Controller ◽  
Automatic Voltage Regulator

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes.

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