Title :
Stochastic neural adaptive control using state space innovations model
Author :
Ho, Tuan I. ; Ho, Son T. ; Bialasiewicz, Jan T. ; Wall, Edward T.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Colorado Univ., Denver, CO, USA
Abstract :
An attempt is made to contribute to the unification of traditional state space adaptive control and neural system theory. A stochastic neural adaptive control algorithm, where the system identification is based on the state space innovations model, which employs a neural network architecture, is presented. The control law is derived from a quadratic (one-step-ahead prediction) performance index, which in combination with the neural identification constitutes an excellent neural adaptive control algorithm
Keywords :
adaptive control; identification; neural nets; performance index; state-space methods; stochastic systems; identification; quadratic one-step-ahead prediction performance index; state space innovations model; stochastic neural adaptive control; Adaptive control; Aerodynamics; Neural networks; Performance analysis; State estimation; State-space methods; Stochastic processes; Stochastic systems; System identification; Technological innovation;
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
DOI :
10.1109/IJCNN.1991.170740
