Adaptive control of continuous time systems with convex/concave parametrization
Automatica (Journal of IFAC)
Fuzzy adaptive control for a class of nonlinear systems
Fuzzy Sets and Systems
Convergence Rates of Approximation by Translates
Convergence Rates of Approximation by Translates
Robust adaptive control using a universal approximator with application to vehicle motion control for ivhs
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach
IEEE Transactions on Fuzzy Systems
Approximation accuracy analysis of fuzzy systems as function approximators
IEEE Transactions on Fuzzy Systems
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Fuzzy controller design for a class of model reference adaptive systems
International Journal of Computer Applications in Technology
Fuzzy model reference adaptive control system
ICAI'05/MCBC'05/AMTA'05/MCBE'05 Proceedings of the 6th WSEAS international conference on Automation & information, and 6th WSEAS international conference on mathematics and computers in biology and chemistry, and 6th WSEAS international conference on acoustics and music: theory and applications, and 6th WSEAS international conference on Mathematics and computers in business and economics
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Recently, various adaptive fuzzy control schemes have been proposed to deal with nonlinear systems whose dynamics are poorly understood by using the parameterized fuzzy approximators. However, most of the schemes presented so far can only tune the parameters, which appear linearly in the parameterized fuzzy approximators. The major disadvantage is that the desired approximation error may not be warranted and consequently, the control performance could be influenced. In this paper, we tune not only the linear parameters but also the parameters, which appear nonlinearly in the fuzzy approximators, to reduce the approximation error and to improve control performance. The proposed adaptive controller ensures global stability of the overall adaptive system and achieves desired tracking.