Title :
Tuning of a PID controller using immune network model and fuzzy set
Author_Institution :
Dept. of I&C, Hanbat Nat. Univ., Seoul
Abstract :
This paper suggests that the immune network algorithm based on fuzzy sets can effectively be used in tuning of a PID controller for multivariable processes or nonlinear processes. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. The result of study shows the artificial immune network based on fuzzy set can effectively be used to tune the nonlinear process or the multivariable process, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods, against the noise or disturbance, various inputs, and coupling action between loops
Keywords :
artificial intelligence; control system analysis; control system synthesis; evolutionary computation; fuzzy set theory; multivariable control systems; nonlinear control systems; three-term control; tuning; PID controller tuning; antibodies communication; artificial immune network; control design; control simulation; fuzzy set; immune network algorithm; immune network model; large-scale network; multivariable processes; nonlinear processes; parallel decentralized processing mechanism; stimulation chains; suppression chains; Application software; Artificial intelligence; Artificial neural networks; Control systems; Electrical equipment industry; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Intelligent systems; Three-term control;
Conference_Titel :
Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
Conference_Location :
Pusan
Print_ISBN :
0-7803-7090-2
DOI :
10.1109/ISIE.2001.931956