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Reliable Control Of Discrete-time Fuzzy Systems

Posted on:2017-03-12Degree:MasterType:Thesis
Country:ChinaCandidate:Y D HeFull Text:PDF
GTID:2348330503987234Subject:Control Science and Engineering
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The structure and function of the modern engineering control systems have been more and more complex, so that the reliability plays an important role in keeping normal operation of control systems. The failures of sensors, actuators or other components of the systems may cause degradation of performance, what is worse, the stability of the systems may be destroyed. In order to solve the problem, fault tolerant control is known as a significant way which is proved to be effective. On the other hand, since the actual systems generally have strong nonlinearity, the classical linear control theory is no longer applicable to analysis and synthesis of such systems. In recent years, the Takagi-Sugeno(T-S) fuzzy model has been proven to be an effective tool for the research of nonlinear systems. Thanks to the special structure of the T-S fuzzy model, researchers can not only use it to approximate the complex nonlinear function, but also can adequately combine the flexible fuzzy logic theory and fruitful linear multivariable system theory into a unified framework to solve the control problem of nonlinear systems.This paper focuses on the reliable and robust H? feedback control for a class of discrete-time nonlinear systems with Markovian jumping actuator faults. The nonlinear plant is expressed by a discrete-time T-S fuzzy affine model with parametric uncertainties, and a Markov process is adopted to characterize the actuator-fault phenomenon, and in order to reduce the conservative of the results, utilizing the Lyapunov stability theory, we choose a piecewise Markovian-Lyapunov function, combined with S-procedure and some linear matrix inequality(LMI) techniques, the reliable piecewise robust controller synthesis is developed for the underlying systems. It is shown that the desired reliable controller gains can be obtained by solving a set of linear matrix inequalities. The main results are as follows:Firstly, the paper studies the reliable and robust H? state feedback control for discrete-time T-S fuzzy affine systems with Markovian jumping actuator faults. Based on the premise variables and membership functions, the system model is rewritten as an equivalent piecewise T-S fuzzy affine model. Based on a piecewise Markovian-Lyapunov function combined with S-procedure and some LMIs techniques, the reliable robust H? piecewise state feedback controller synthesis is developed, which can ensure that the closed-loop system is stable and can achieve satisfactory performance.Secondly, we study the reliable and robust H? piecewise output feedback control for discrete-time T-S fuzzy affine systems. First, it assumes that the system output matrix is full row rank without parameter uncertainties, a general output feedback reliable controller synthesis method is proposed, which makes the system stable and satisfy the given H? performance. Then in order to get a controller design method which is more flexible in application without additional assumptions, an augmented system which is equivalent to the original system model is adopted to investigate the problem of reliable output feedback control for nonlinear system. Based on this model, the assumptions mentioned above are not necessary.Thirdly, the observer-based time delay independent reliable piecewise output feedback controller synthesis of discrete-time T-S fuzzy affine dynamic system with time delay is taken in account. System states are not always available, for the purpose of solving the difficulties in application of state feedback control, an asynchronous piecewise observer is used to estimate the states of the plant, then this estimation is used as feedback signal instead of the system states, the reliable delay independent controller synthesis method is developed.
Keywords/Search Tags:Reliable control, T-S fuzzy affine model, Actuator fault, Piecewise Markovian-Lyapunov function, Linear matrix inequality
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