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Research On Adaptive Fuzzy Control For Nonaffine Nonlinear Uncertain Systemes And Applications

Posted on:2012-09-22Degree:DoctorType:Dissertation
Country:ChinaCandidate:J WenFull Text:PDF
GTID:1118330362958250Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
Nonaffine nonlinear systems widely exist in real world. Taking into account that the actual system is often uncertain, how to control the nonaffine nonlinear uncertain systems is an innovative and challenging subject and has important theoretical and practical value. To solve this problem, based on the universal approximation properties of fuzzy logic system (FLS), this thesis systematically studies a series of adaptive fuzzy control strategies for several types of nonaffine nonlinear systems.Adaptive state-feedback and output-feedback fuzzy controllers are developed for a class of single input single output (SISO) nonaffine nonlinear uncertain systems. In the situation that the system states are observable, a fuzzy logic system is employed to approximate the unknown nonlinearity, the adjustable parameters in FLS are updated byσadaptive law and the proof of boundedness of parameters is given. A robust control term is introduced to compensate the approximation error and disturbances to make the tracking error converge to zero. In order to avoid chattering of the control input,a tanh function is used in robust term and the corresponding adaptive law is redesigned. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the tracking error eventually converges to a small neighborhood of zero. The developed design scheme is applied to Duffing-Holmes system, Genesio system and Sprott circuit chaotic system. Simulation results demonstrate the effectiveness of the proposed approach. In additon, it is assumed that the system states are unavailable, then a linear error observer is employed to estimate output errors and states. An adaptive controller is designed by using the observed values of errors and states, so that the whole closed loop system is stable in the sense of Lyapunov. Duffing-Holmes chaotic system is used to emphasize the effectiveness of the approach.Based on backstepping approach, a robust adaptive fuzzy control scheme is presented for a class of strict-feedback nonaffine nonlinear systems. Approximation errors of fuzzy systems are only required norm-bounded, and the online computation quantity is reduced by tuning estimations of the unknown bounds online. An additional adaptive term is employed to compensation approximation errors and disturbances. The stability of the whole closed loop system is proved via Lyapunov method. Chua's circuit sytem and R?ssler chaotic system is presented to illustrate the feasibility and effectiveness of the proposed control technique.□An adaptive fuzzy control schemes is proposed for a class of multi-input multi-output (MIMO) nonaffine nonlinear systems in block-triangular forms. The MIMO systems consist of interconnected subsystems, Lyapunov function is constructed for each subsystem to design the corresponding control law. Finally, Lyapunov function of the whole system is designed so that the all the signals in the closed-loop system are bounded and the tracking error eventually converges to a small neighborhood of zero. The developed design scheme is applied to Lorenz system, permanent-magnet synchronous motor system, Lüsystem, Liu system and hyperchaotic R?ssler system. Simulation results demonstrate the effectiveness of the proposed approach.An adaptive fuzzy control schemes is proposed for a class of strict-feedback nonaffine nonlinear systems with time delays, the unknown time delays are compensated for using appropriate Lyapunov-Krasovskii functionals, the singularity generated in the process of compensation is overcome by the using of tanh function. The proposed controller guarantees that all closed-loop signals remain bounded. R?ssler chaotic system with time delay is given to illustrate the design procedure and performance of the proposed method.Parameter selection is another important problem for controller design. Thus, in the last part of the thesis, taking the complexity of FLS, tracking error and control oscillation as object functions, an elitist preserved genetic algorithm is employed to search for the optimum parameters by designing corresponding genetic operators. A simulation example is presented to illustrate the feasibility and effectiveness of the proposed control technique.
Keywords/Search Tags:Nonaffine nonlinear systems, Adaptive fuzzy control, Strict-feedback system, Backstepping approach, Lyapunov-Krasovskii functionals, nonlinar systems with time delays, tanh function, Chaotic system
PDF Full Text Request
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