Title :
Optimal control for nonlinear systems by a neural controller of the state feedback type
Author :
Shimizu, Kiyotaka ; Ohtani, Masami
Author_Institution :
Fac. of Sci. & Technol., Keio Univ., Yokohama, Japan
Abstract :
This paper is concerned with designing a neuro-controller for optimal control of nonlinear systems. The neuro-controller approximates the optimal state feedback control law for the nonlinear systems. The neuro-controller consists of a multilayer neural network and its matrices of connection weights are optimized so that the performance function is minimized. Optimality conditions for the neuro-controller is derived first and then optimal values of the matrices of connection weights are calculated by a steepest descent method with error backpropagation algorithm. Learning of the weights are carried out by off-line scheme
Keywords :
control system synthesis; feedforward neural nets; neurocontrollers; nonlinear systems; optimal control; optimisation; state feedback; connection weight matrices; error backpropagation; function optimisation; multilayer neural network; neural controller; nonlinear systems; optimal control; state feedback; steepest descent method; Control system synthesis; Control systems; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems; Open loop systems; Optimal control; Optimization methods; State feedback;
Conference_Titel :
Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-3590-2
DOI :
10.1109/CDC.1996.573654
