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Adaptive output feedback tracking controller for a class of uncertain strict feedback nonlinear systems in the absence of state measurements
Authors:Shahin Salehi
Affiliation:Department of Measurement and Automation , Petroleum University of Technology , Tehran, Iran
Abstract:In this article, design of an adaptive control scheme for a class of uncertain single-input single-output systems in strict feedback form via a backstepping technique has been proposed. It is assumed that system output and its derivatives are available. By virtue of the observability concept, it is shown that for this class of systems there exists a one-to-one map, which maps output and its derivatives to system states. By means of this mapping and using linearly parametrised approximators, such as fuzzy logic systems or neural networks, the uncertain nonlinear dynamics and unavailable states are estimated. The proposed adaptive controller guarantees that the closed-loop system is uniformly ultimately bounded and the influence of minimum approximation error on the L 2-norm of the output tracking error is attenuated arbitrarily. The effectiveness of the proposed scheme has been demonstrated through simulation results.
Keywords:adaptive control  backstepping control  neural network  fuzzy logic  uncertain nonlinear systems
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