Fuzzy Adaptive Output Feedback Control For Stochastic Uncertain Nonlinear Systems

Under the framework of fuzzy logic systems (FLS), adaptive fuzzy Backstepping control and dynamic surface control technique (DSC), designed fuzzy state observer and adaptive fuzzy Backstepping output-feedback controller for some classes of stochastic systems without satisfying the matching condition and the measurements of the states. This thesis systematically studied stability analysis of the closed-loop system. The main contributions are as follows:1. Two adaptive fuzzy output feedback control approaches are proposed for a class of single-input-single-output (SISO) stochastic nonlinear systems without the measurements of the states, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, by combining the adaptive backstepping technique with fuzzy adaptive control design, an adaptive controller is designed. On the basis of above these, the dynamic surface control (DSC) technique is introduced, and a simplified adaptive controller is designed. It is proved that these control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SUUB) in probability, the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. The simulation examples are provided to show the effectiveness of the proposed approaches.2. Two adaptive fuzzy output feedback control approaches are proposed for a class of strict-feedback stochastic nonlinear systems with time delays and immeasurable states, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, by combining the adaptive backstepping technique with fuzzy adaptive control design, an adaptive controller is designed. On the basis of above these, the dynamic surface control (DSC) technique is introduced, and a simplified adaptive controller is designed. It is proved that these control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SUUB) in probability, the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. The simulation examples are provided to show the effectiveness of the proposed approaches.3. Two adaptive fuzzy output feedback control approaches are proposed for a class of multi-input and multi-output (MIMO) stochastic nonlinear systems without the measurements of the states, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, by combining the adaptive backstepping technique with fuzzy adaptive control design, an adaptive controller is designed. On the basis of above these, the dynamic surface control (DSC) technique is introduced, and a simplified adaptive controller is designed. It is proved that these control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SUUB) in probability, the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. The simulation examples are provided to show the effectiveness of the proposed approaches.4. Two adaptive fuzzy decentralized output feedback control approaches are proposed for a class of large-scale stochastic nonlinear systems without the measurements of the states, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, by combining the adaptive backstepping technique with fuzzy adaptive control design, an adaptive decentralized controller is designed. On the basis of above these, the dynamic surface control (DSC) technique is introduced, and a simplified adaptive decentralized controller is designed. It is proved that these control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SUUB) in probability, the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. The simulation examples are provided to show the effectiveness of the proposed approaches.