Abstract
In this paper, an adaptive fuzzy-neural controller for a class of unknown nonlinear dynamical systems is proposed. The objective of the control is to track a bounded reference signal. This objective is achieved through fuzzy-neural networks. The structure of the fuzzyneural model is used to approximate the linearization of the nonlinear system. A composite law is proposed in order to prevent parameter drift. Also, the composite law can be applied to other robust adaptive control schemes. In addition, for the purpose of confining the states of the system to the allowed regions, the variable structure control via fuzzy logic is introduced. Therefore, the adaptive controller is robust with respect to unmodeled dynamics, disturbances and modeling errors. Finally, an application of the method to the inverted pendulum stabilizing problem is discussed.
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