Title :
Robust backstepping control of nonlinear systems in discrete-time using multilayer neural networks
Author_Institution :
Automated Analysis Corp., Peoria, IL., USA
Abstract :
A multilayer neural network (NN) controller for the robust backstepping control of nonlinear systems in discrete-time is presented. Control action is employed to achieve tracking performance for unknown nonlinear systems. Tuning methods are derived for the multilayer NN based on the delta rule. Uniform ultimate boundedness of the tracking error and the weight estimates are presented without using the PE condition. No learning phase is needed for the NN and initialization of the network weights is straightforward
Keywords :
discrete time systems; multilayer perceptrons; neurocontrollers; nonlinear control systems; robust control; tracking; tuning; uncertain systems; control action; multilayer neural networks; nonlinear systems; robust backstepping control; tracking error; tracking performance; tuning methods; uniform ultimate boundedness; weight estimates; Adaptive control; Automatic control; Backstepping; Control systems; Intelligent networks; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems; Robust control;
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.1997.650672
