Title :
Nonlinear adaptive control using neural networks: estimation with a smoothed form of simultaneous perturbation gradient approximation
Author :
Spall, James C. ; Cristion, John A.
Author_Institution :
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
fDate :
29 June-1 July 1994
Abstract :
This is a condensed version of a full length interdisciplinary paper spanning the fields of control statistics, neural networks and optimisation. In this paper only the following two topics are considered: 1) consider the problem of developing adaptive controllers for general dynamic systems with unknown governing equations and develop a solution for an important class of such problems; and 2) introduce a modification to simultaneous perturbation stochastic approximation that is based on smoothing gradient approximations across iterations and illustrate this modification on the neural net based control problem.
Keywords :
adaptive control; approximation theory; neural nets; nonlinear control systems; perturbation techniques; dynamic systems; neural networks; nonlinear adaptive control; perturbation gradient approximation; stochastic approximation; Adaptive control; Artificial neural networks; Control systems; Error correction; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear equations; Open loop systems; Stochastic systems;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.735021