Title
Adaptive neural network tracking control with disturbance attenuation for multiple-input nonlinear systems.
Abstract
A switching adaptive neural network controller for multiple-input nonlinear, affine in the control dynamical systems with unknown nonlinearities is designed, capable of arbitrarily attenuating L(2) or L(infinity) external disturbances. In the absence of disturbances, a uniform ultimate boundedness property of the tracking error with respect to an arbitrarily small set around the origin is guaranteed, as well as the uniform boundedness of all the signals in the closed loop. The proposed switching adaptive controller effectively avoids possible division by zero, while guaranteeing the continuity of switching. In this way, problems connected to existence of solutions and chattering phenomena are alleviated. Simulations illustrate the approach.
Year
DOI
Venue
2009
10.1109/TNN.2008.2005598
IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council
Keywords
Field
DocType
disturbance attenuation,multiple-input nonlinear dynamical system,neurocontrollers,unknown nonlinearity design,time-varying systems,control system synthesis,closed loop system,nonlinear dynamical systems,neural adaptive control,adaptive control,tracking,uniform ultimate boundedness property,control nonlinearities,unknown lyapunov function,switching adaptive neural network tracking control,switching adaptive control,closed loop systems,lyapunov methods
Control theory,Nonlinear system,Computer science,Nonlinear control,Control theory,Adaptive system,Uniform boundedness,Dynamical systems theory,Adaptive control,Tracking error
Journal
Volume
Issue
ISSN
20
2
1941-0093
Citations 
PageRank 
References 
2
0.39
23
Authors
2
Name
Order
Citations
PageRank
Artemis K. Kostarigka1452.25
George A. Rovithakis258152.21