Wavelet Adaptive Observer Based Control for a Class of Uncertain Time Delay Nonlinear Systems with Input Constraints

This Paper investigates the mean to design the observer and observer based controllers for a class of delayed nonlinear systems with Lipschitz conditions and unknown dynamics subjected to input constraints. A new design approach of full order wavelet based adaptive observer is proposed. Wavelet neural networks (WNN), which are having superior learning capability in comparison to conventional neural networks, are used as system identification tool. Using the feedback control, based on reconstructed states, the behavior of closed loop system is investigated. The fact that the uncertain time delayed system with observer based control converges to the small neighborhood of the origin is established through Lyapunov-Krasovskii functional. A numerical example is provided to verify the effectiveness of theoretical development.