Please use this identifier to cite or link to this item: https://doi.org/10.1109/.2005.1467031
Title: Adaptive neural control of non-affine pure-feedback systems
Authors: Wang, G.
Hill, D.J.
Ge, S.S. 
Issue Date: 2005
Source: Wang, G.,Hill, D.J.,Ge, S.S. (2005). Adaptive neural control of non-affine pure-feedback systems. Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05 2005 : 298-303. ScholarBank@NUS Repository. https://doi.org/10.1109/.2005.1467031
Abstract: 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. ©2005 IEEE.
Source Title: Proceedings of the 20th IEEE International Symposium on Intelligent Control, ISIC '05 and the 13th Mediterranean Conference on Control and Automation, MED '05
URI: http://scholarbank.nus.edu.sg/handle/10635/69192
ISBN: 0780389360
DOI: 10.1109/.2005.1467031
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