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Adaptive Weighted Control for A Class of Nonlinear Systems

In this paper, an adaptive weighted control method for Hammerstein-Wiener nonlinear systems has been derived by considering the tracking of the references while simultaneously minimizing the control effort. Based on the parameterization model of Hammerstein-Wiener systems, parameter adaptation is implemented throughout the use of internal variable estimations. Based on these estimates, the control law is designed by analyzing a new criterion function which takes the whole nonlinear systems into account and penalizes the excessive control action according to the nonlinear gains. By simplifying the above complex control law, we obtain a simple adaptive weighted control algorithm, which reduces overshoot and oscillation effectively. The closed-loop stability and output tracking properties are analyzed to demonstrate the proposed novel concepts. Illustrative simulation results are presented to verify the effectiveness of the proposed algorithms.