Wavelet Based Adaptive Tracking Control for Uncertain Nonlinear Systems with Input Constraints

This paper proposes a wavelet based adaptive tracking controller for uncertain nonlinear systems. The controller is designed to provide the desired performance in the presence of actuator constraints. Proposed controller comprises of wavelet based tracking controller and a robust controller. Wavelet tracking controller is the principal controller while robust controller is designed to achieve the desired performance by attenuating the effect of approximation error caused by wavelet identifier. Wavelet networks, which are having superior learning capability in comparison to conventional neural network, are used for the approximation of unknown system dynamics. Also the adaptation laws are derived in the sense of Lyapunov function assuring the stability of the system. To deal with the actuator constraints, the system is augmented with additional wavelet network to work as a saturation compensator so as to recover the unconstrained response rapidly while preserving the system stability.