Simulation and Design of Numeral Fuzzy PID Controller System
Yin Yun-hua
Abstract
Yin Yun-hua
Abstract
Traditional PID controller suffers a problem that it can't regulate parameters automatically and has some use limitations.In this paper,based on PID controller and taking error and error change as inputs,a fuzzy reasoning method is utilized to realize automatic regulation of PID parameters,and the controller in some two-rank delay system is designed and simulated with MATLAB.The result of simulation indicates that the adaptive fuzzy PID controller is superior to traditional PID controller and it can improve the dynamic and static properties of the control system.This mixing system combines convenience of PID control with flexibleness and robustness of fuzzy control,and has a strong practical significance and a high reference value for further applications.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Traditional PID controller suffers a problem that it can't regulate parameters automatically and has some use limitations.In this paper,based on PID controller and taking error and error change as inputs,a fuzzy reasoning method is utilized to realize automatic regulation of PID parameters,and the controller in some two-rank delay system is designed and simulated with MATLAB.The result of simulation indicates that the adaptive fuzzy PID controller is superior to traditional PID controller and it can improve the dynamic and static properties of the control system.This mixing system combines convenience of PID control with flexibleness and robustness of fuzzy control,and has a strong practical significance and a high reference value for further applications.
Key concepts: PID controller, Control theory (sociology), Robustness (evolution), Control engineering, MATLAB, Computer science, Fuzzy logic, Control system