Title
Neural adaptive regulation of unknown nonlinear dynamical systems.
Abstract
With this paper we extend our previous work on the subject, by including the case where the number of control inputs is different from the number of states which is frequently faced in control engineering problems. Uniform ultimate boundedness of the state and uniform boundedness of all other signals in the closed loop is guaranteed. Robustness of our algorithm due to the presence of a modeling error term which has linear growth with unknown growth coefficient is also established. Finally, the applicability of our control scheme is highlighted via simulation results.
Year
DOI
Venue
1997
10.1109/3477.623234
IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Keywords
Field
DocType
robustness,neural networks,adaptive regulation,modeling error term,neurocontrollers,robust control,closed loop,nonlinear dynamical systems,adaptive control,boundedness,closed loop systems
Mathematical optimization,Nonlinear control,Computer science,Control theory,Uniform boundedness,Robustness (computer science),Automatic control,Adaptive control,Robust control,Variable structure control,Sliding mode control
Journal
Volume
Issue
ISSN
27
5
1083-4419
Citations 
PageRank 
References 
23
1.86
14
Authors
2
Name
Order
Citations
PageRank
George A. Rovithakis158152.21
manolis a christodoulou246159.94