Premium
A Novel Robust Pid Controller Design By Fuzzy Neural Network
Author(s) -
Lee ChingHung,
Lee YiHsiung,
Teng ChingCheng
Publication year - 2002
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2002.tb00084.x
Subject(s) - pid controller , robustness (evolution) , control theory (sociology) , parametric statistics , artificial neural network , phase margin , control engineering , robust control , fuzzy logic , computer science , engineering , control system , artificial intelligence , control (management) , mathematics , temperature control , bandwidth (computing) , amplifier , computer network , biochemistry , chemistry , statistics , electrical engineering , operational amplifier , gene
In this paper, we propose a robust PID controller tuning method for parametric uncertainty systems (or interval plant family) using fuzzy neural networks (FNNs). This robust controller is based on robust gain and phase margin (GM/PM) specifications that satisfy user requirements. Here, the FNN system is used to identify the relation between the PID controller parameters and robust GM/PM. We can use the trained FNN system to determine the parameters of the PID controllers in order to satisfy robust GM/PM specifications that guarantee robustness and performance. Simulation results are shown to illustrate the effectiveness of the robust controller scheme.