Calculation of PID controller parameters by using a fuzzy neural network.
In this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (Ms). The FNN system is used to identify the relationship between plant model and controller parameters based on IAE and Ms. To derive the tuning rule, the dominant pole assignment method is applied to simplify our optimization processes. Therefore, the FNN system is used to automatically tune the PID controller for different system parameters so that neither theoretical methods nor numerical methods need be used. Moreover, the FNN-based formula can modify the controller to meet our specification when the system model changes. A simulation result for applying to the motor position control problem is given to demonstrate the effectiveness of our approach.
Lee
Ching-Hung
CH
Department of Electrical Engineering, Yuan Ze University 135 Yuan Tung Rd, Chung-Li, Taoyuan 320, Taiwan, Republic of China. chlee@saturn.yzu.edu.tw
Teng
Ching-Cheng
CC
D000465:Algorithms; D003198:Computer Simulation; D004867:Equipment Design / Q000379:methods; D005246:Feedback; D017143:Fuzzy Logic; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012680:Sensitivity and Specificity