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Adaptive Neural Control of Non-Affine Pure-Feedback Systems

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3 Author(s)
Cong Wang ; Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou ; Hill, D.J. ; Ge, S.S.

Controlling non-affine nonlinear systems is a challenging problem in the control community. In this paper, an adaptive neural control approach is presented for the completely non-affine pure-feedback system with only one mild assumption. By combining adaptive neural design with input-to-state stability (ISS) analysis and the small-gain theorem, the difficulty in controlling non-affine pure-feedback system is overcome by achieving the so-called "ISS-modularity" of the controller-estimator. The ISS-modular approach provides an effective way for controlling non-affine nonlinear systems with uncertainties. Simulation studies are included to demonstrate the effectiveness of the proposed approach

Published in:

Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation

Date of Conference:

27-29 June 2005