Title :
Design of a robust neural controller for a specified plant using genetic algorithms approach
Author_Institution :
Dept. of Electr. Eng., Da-Yeh Univ., ChungHwa, Taiwan
Abstract :
Applications of soft computing (SC) concept to control systems design are appealing to all control designers. Discussions on how to design neural controllers (NC) for control system design are still not plentiful. In these paper, genetic algorithms (GA) approach is used for finding weights and bias of a NC. From the simulation results, robustness to the plant parameters is preserved.
Keywords :
control systems; genetic algorithms; model reference adaptive control systems; neurocontrollers; robust control; control systems design; genetic algorithms; plant parameters; robust neural controller; robustness; soft computing; Algorithm design and analysis; Cities and towns; Computer applications; Control system synthesis; Control systems; Genetic algorithms; Neural networks; Open loop systems; Robust control; System identification;
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2003. CIMSA '03. 2003 IEEE International Symposium on
Print_ISBN :
0-7803-7783-4
DOI :
10.1109/CIMSA.2003.1227233
