Adaptive neural compensation control for input-delay nonlinear systems by passive approach

This paper focuses on the design of passive controller with adaptive neural compensation for uncertain strict-feedback nonlinear systems with input-delay. For local linearization model, the delay-dependent gamma-passive control is presented. Then, gamma-passive control law of local linear model is decomposed as the virtual control of sub-systems by backstepping. In order to compensate the nonlinear dynamics, the adaptive neural model is proposed. The NN weights are turned on-line by Lyapunov stability theory with no prior training. The design procedure of whole systems is a combination of local gamma-passive control and adaptive neural network compensation techniques.