Fuzzy Adaptive Backstepping Dynamic Surface Fault-tolerant Control Of Nonlinear Systems

The problems of fuzzy modeling for some classes of nonlinear systems with actuatorfaults by fuzzy logic systems are addressed in the thesis. By combining fuzzy control theory,adaptive backstepping control theory and fault-tolerant control theory, the design problems ofthe fuzzy state observers and the fuzzy adaptive fault-tolerant controllers are studied, and thefuzzy adaptive backstepping fault-tolerant control approaches are developed. It systematicallystudies stabilization problems of the closed-loop control systems. The main contributions areas follows:(1) For a class of multiple-input and single-output nonlinear systems with actuator faultsand unmeasured states, fuzzy logic systems are employed to approximate the unknownnonlinear functions and a fuzzy state observer is developed for estimating the systematicstates. By combining the backstepping technique with the dynamic surface control approachand the predefined performance functions, a fuzzy adaptive fault-tolerant controller isconstructed. Based on the Lyapunov stability theory, it is proved that all the signals of theclosed-loop system are bounded and the tracking errors converge to a small neighbourhood ofzero. The computer simulation results indicate the effectiveness of the proposed controlapproaches.(2) For a class of multiple-input and single-output nonlinear systems with actuator faults,unmodeled dynamics and unmeasured states, fuzzy logic systems are employed toapproximate unknown nonlinear functions and a fuzzy state observer is established toestimate the systematic states. By combining adaptive backstepping technique with changingsupplying function technique and the nonlinear fault-tolerant control theory, a fuzzy adaptivefault-tolerant controller is developed. Based on the Lyapunov stability theory, it is proved thatall the signals of the closed-loop system are bounded and the tracking errors converge to asmall neighbourhood of zero. The computer simulation result illustrates the effectiveness ofthe proposed control approach.(3) For a class of uncertain multiple-input and multiple-output nonlinear systems withactuator faults and immeasurable states, fuzzy logic systems are employed to approximate theunknown nonlinear functions and a fuzzy state observer is developed for estimating thesystematic states. Combining the backstepping technique with the dynamic surface controlapproach, a fuzzy adaptive fault-tolerant controller is constructed. Based on the Lyapunovstability theory, it is proved that all the signals of the closed-loop system are bounded and thetracking errors converge to a small neighborhood of the origin. The computer simulationresult indicates the effectiveness of the proposed control approach.(4) For a class of uncertain nonlinear large-scale systems with actuator faults andmeasured states, fuzzy logic systems are employed to approximate the unknown nonlinearfunctions. A fuzzy adaptive decentralize faults-tolerant controller is developed by combining the backstepping technique and the dynamic surface control approach. Based on the Lyapunovstability theory, it is proved that all the signals of the closed-loop systems are bounded and thetracking errors converge to a small neighbourhood of zero. The computer simulation resultindicates the effectiveness of the proposed control approach.(5) For a class of nonlinear large-scale systems with the unmodeled dynamics, actuatorfaults and immeasurable states, fuzzy logic systems are employed to approximate theunknown nonlinear functions and a fuzzy state observer is designed to estimate theunmeasured states. By using the backstepping technique and the dynamic surface controlapproach and combining with the changing supply function technique, a fuzzy adaptivefault-tolerant controller is developed. Based on the Lyapunov stability theory, it is proved thatall the signals of the closed-loop systems are bounded and the tracking errors converge to asmall neighbourhood of zero. The computer simulation result indicates the effectiveness ofthe proposed control approach.