Title :
Robust control for nonlinear systems by universal learning network considering fuzzy criterion and second order derivatives
Author :
Ohbayashi, Masanao ; Hirasawa, Kotaro ; Toshimitsu, Katsuyuki ; Murata, Junichi ; Hu, Jinglu
Author_Institution :
Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan
Abstract :
Control systems using neural networks have been used in many fields, but some problems remain unsolved. One of the problems which should be overcome is to enhance the robustness of the neural network control systems. In the paper, a robust control method is proposed, which is based on the second order derivatives of the universal learning network and fuzzy criterion function
Keywords :
control system synthesis; learning (artificial intelligence); neurocontrollers; nonlinear control systems; robust control; fuzzy criterion; neural network control systems; nonlinear systems; robust control; second order derivatives; universal learning network; Control systems; Design methodology; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Neural networks; Nonlinear systems; Robust control; Robustness;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.685902
