Adaptive control of output constrained nonlinear systems based on nonlinear mapping

In this paper, an adaptive dynamic surface output feedback control scheme is proposed for a class of nonlinear systems with unmodeled dynamics and output constraint. A description based on Lyapunov function for unmodeled dynamics is proposed to handle dynamic uncertainties. An one to one nonlinear mapping is introduced to solve output constrained problem. K-filters is introduced to estimate the unmeasured states. The radial basis function neural networks are utilized to approximate unknown nonlinear continuous function. It is shown that all the signals in the closed-loop system are bounded, and the output constraint is not violated. Simulation results demonstrate the effectiveness of the proposed approach.