Title :
A stable neural network-based adaptive control scheme for a class of nonlinear plants
Author :
Boskovic, Jovan D.
Author_Institution :
Scientific Syst. Co. Inc., Woburn, MA., USA
Abstract :
A stable adaptive neural network control scheme, based on that suggested in Boskovic (1997), is designed for a class of second-order unknown nonlinear plants. It is shown that a two-layer neural network, built using a rational activation function, results in a convenient parametrization which enables the generation of stable adaptive laws. The corresponding well-tuned neural network controller results in the stable overall system as demonstrated using a suitably chosen Lyapunov function. It is also shown that this controller can be efficiently combined with an indirect VS controller within the framework of stable multiple model-based adaptive control to achieve the control objective and assure favorable performance of the overall closed-loop system
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; model reference adaptive control systems; multilayer perceptrons; neurocontrollers; nonlinear control systems; stability; uncertain systems; Lyapunov function; closed-loop system; indirect VS controller; rational activation function; second-order unknown nonlinear plants; stable multiple model-based adaptive control; stable neural network-based adaptive control scheme; two-layer neural network; well-tuned neural network controller; Adaptive control; Adaptive systems; Artificial neural networks; Control systems; Lyapunov method; Multi-layer neural network; Neural networks; Nonlinear control systems; Programmable control; Trajectory;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.650670