Adaptive Output Feedback Control of a Class of Nonlinear Systems Using Neural Networks
نویسندگان
چکیده
This paper presents tools for the design of a neural network based adaptive output feedback controller for a class of nonlinear MIMO systems without zero dynamics. Each of the outputs is assumed to have relative degree less or equal to 2. Under the condition that the output functional dependence is unknown, a neural network based adaptive observer is designed to estimate the derivatives of the outputs. Subsequently, this observer is integrated into an NN based adaptive controller architecture. Conditions are derived which guarantee the boundedness of all the errors and NN weights in the closed loop system. Stability analysis reveals simultaneous learning rules for both the adaptive NN observer and adaptive NN controller.
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