Journal
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
Volume 21, Issue 5, Pages 527-541Publisher
WILEY-BLACKWELL
DOI: 10.1002/rnc.1608
Keywords
adaptive control; neural networks; nonlinear control; pure-feedback systems
Funding
- National Nature Science Foundation of China [60674037]
- Program for Liaoning Excellent Talents in Universities [2009R06]
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In this paper, by incorporating the dynamic surface control technique into a neural network-based adaptive control design framework, we have developed a backstepping-based control design for a class of nonlinear systems in pure-feedback form with arbitrary uncertainty. The circular design problem which may exist in pure-feedback systems is overcome. In addition, our development is able to eliminate the problem of 'explosion of complexity' inherent in the existing backstepping-based methods. A stability analysis is given, which shows that our control law can guarantee the semi-global uniformly ultimate boundedness of the solution of the closed-loop system, and makes the tracking error arbitrarily small. Moreover, the proposed control design scheme can also be directly applied to the strict-feedback nonlinear systems with arbitrary uncertainty. Copyright (C) 2010 John Wiley & Sons, Ltd.
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