Adaptive Fuzzy Backstepping Output-feedback Control For Nonlinear Systems Based On High-gain Observer

Under the framework of Lyapunov stability theory, adaptive fuzzy Backstepping control, fuzzy approximate theory, this thesis designed adaptive high-gain observer and adaptive fuzzy Backstepping output-feedback controller for some classes of uncertain dynamical systems with completely unknown functions, without the measurements of the states. This thesis systematically studied stability analysis of the closed-loop systems and convergences problems for some classes of nonlinear systems without satisfying the matching condition. The main contributions are as follows:1. An adaptive fuzzy Backstepping output-feedback control approach is proposed for a class of SISO uncertain dynamical systems with completely unknown functions, without the measurements of the states. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and an adaptive high-gain observer is developed to estimate the unmeasured states. By theoretical analysis, the closed-loop control system is proven to be semiglobal1y uniformly ultimately bounded(SUBB), with the observer errors and tracking error converge to a small neighborhood of the origin by appropriate choice of the design parameters.2. An adaptive fuzzy Backstepping output-feedback control approach is proposed for a class of SISO uncertain dynamical systems with completely unknown functions and unmeasurable unmodeled dynamics without the measurements of the states. Use ynamical signal to solve the unmeasurable unmodeled dynamics.Using the designed high-gain observer, and combining the fuzzy adaptive control theory with Backstepping approach, an adaptive fuzzy Backstepping output-feedback control scheme is developed for SISO nonlinear uncertain systems. By theoretical analysis, the closed-loop control system is proven to be SUBB, with the observer errors and tracking error converge to a small neighborhood of the origin by appropriate choice of the design parameters.3. An adaptive fuzzy Backstepping output-feedback control approach is proposed for a class of MIMO uncertain dynamical systems with completely unknown functions without the measurements of the states. Using the designed high-gain observer, and combining the fuzzy adaptive control theory with Backstepping approach, an adaptive fuzzy Backstepping output-feedback control scheme is developed for MIMO nonlinear uncertain systems. By theoretical analysis, the closed-loop control system is proven to be SUBB, with the observer errors and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.4. An adaptive fuzzy Backstepping dynamic surface control (DSC) approach is developed for a class of multi-input and multi-output (MIMO) nonlinear systems with immeasurable states. Using fuzzy logic systems to approximate the unknown nonlinear functions, high-gain observer is designed to estimate the immeasurable states. By combining adaptive Backstepping technique and dynamic surface control technique, an adaptive fuzzy output feedback Backstepping control approach is developed. The proposed control method not only overcomes the problem of"explosion of complexity"inherent in the Backstepping design methods but also the problem of unavailable state measurements. It is proved that the proposed control approach can guarantee all the signals of the closed-loop system are SUUB. The observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.5. An adaptive fuzzy decentralized Backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions, the interconnections mismatched in control inputs, and without the measurements of the states. Using the designed high-gain observer, and combining the fuzzy adaptive control theory with Backstepping approach, an adaptive fuzzy decentralized Backstepping output-feedback control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are SUUB, and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.6. An adaptive fuzzy decentralized Backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,immeasurable states and unknown time delays. Use a Lyapunov-Krasovskii function to solve the unknown time delays. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and an adaptive high-gain observer is developed to estimate the unmeasured states. Using the designed high-gain observer, and combining the fuzzy adaptive control theory with Backstepping approach, a novel adaptive fuzzy decentralized Backstepping output-feedback control scheme is developed. It is proved that the proposed control approach can guarantee all the signals of the closed-loop system are SUUB. The observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.7. The detailed computer simulations are carried out for the proposed adaptive fuzzy Backstepping control approaches in the above by using examples. The simulation results confirm the effectiveness of the proposed control approaches and stability conditions.