DocumentCode :
1559001
Title :
Direct adaptive NN control of a class of nonlinear systems
Author :
Ge, Shuzhi S. ; Wang, Cong
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Volume :
13
Issue :
1
fYear :
2002
fDate :
1/1/2002 12:00:00 AM
Firstpage :
214
Lastpage :
221
Abstract :
In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special property of the affine term, the developed scheme,avoids the controller singularity problem completely. All the signals in the closed loop are guaranteed to be semiglobally uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach
Keywords :
adaptive control; neurocontrollers; nonlinear control systems; closed-loop system; controller singularity; direct adaptive neural-network control; nonlinear systems; nonlinear uncertain systems; strict-feedback form; unknown nonlinearities; Adaptive control; Backstepping; Control nonlinearities; Control systems; Linear feedback control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Stability;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.977306
Filename :
977306
Link To Document :
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