Adaptive Controller Design For Uncertain Nonlinear Systems With Disturbance

Strictly speaking, practical control systems are nonlinear, and always are time-delay. The existence of time delays may degrade the control performance and make the stabilization problem become more difficult. Therefore, the study of nonlinear time-delay systems has an important theoretical and practical significance. The existence of disturbance can debase the system performance, lead the systems to an unstable state when the system is affected by the bounded disturbance and unmodeled dynamics.For a class of nonlinear systems with disturbance, a robust adaptive control algorithm and an adaptive control algorithm based on neural networks are proposed. A controller is designed for a class of Non-affine nonlinear systems. The main work in this thesis is below.By combining backstepping design procedure with robust control strategy and turning the unknown nonlinear function into a new expression, a robust adaptive controller was proposed for a class unknown time-delay nonlinear systems with disturbance. Controller singularity problems were avoided by introducing an appropriate even function. With Lyapunov method, it’s proved that the global uniform ultimate boundedness of all the signals in the closed-loop systems was guaranteed. Validity of the proposed approach was shown in a simulation example.An adaptive neural network controller was designed for a class of unknown time-delay nonlinear systems with disturbance. A radial basis function neural network was chosen to approximate the unknown nonlinear functions in this thesis. The developed control scheme was able to guarantee global uniform ultimate boundedness of all the signals in the closed-loop systems. In this thesis, RBF neural network based adaptive controller for a class of non-affine system was presented. T-S fuzzy model was chosen to approximate the unknown nonlinear functions in this thesis. The complex nonlinear function transform into local linear model by T-S fuzzy model. Inverted pendulum system was employed to demonstrate the effectiveness of the proposed approach on stabilization.