Fuzzy Decentralized Control Of Networked Control Systems

This thesis develops the models of networked control systems (NCS) with different situations based on Takagi-Sugeno (T-S) fuzzy decentralized method. Then, by using parallel distributed compensation (PDC) scheme techniques, we give the design of fuzzy decentralized feedback controllers which ensure the stability of these systems. We consider the stability analysis of these NCS with time-delays and packet dropout via linear matrix inequality (LMI) and Lyapunov stability theory, the constructive condition we presented is expressed as the LMI. The main work of the thesis may be summarized as follows:(1) The first part is concerned with the stability of a class of discrete-time NCS with uncertain network-induced time-delay via fuzzy decentralized control approach. We develop nonlinear systems by using the T-S fuzzy model and then a fuzzy decentralized state feedback controller is designed. A sufficient condition for asymptotic stability of the NCS is obtained by using Lyapunov stability theory. Its constructive condition is expressed as the LMI. Furthermore, a numerical simulation example is exploited to illustrate the result of this chapter.(2) In the second part, we consider the stochastic stability of a class of discrete-time NCS with network-induced packet dropout via fuzzy decentralized control method. Firstly, we define some Bernoulli stochastic variables to describe the data transmission. Secondly, we develop nonlinear systems by using the T-S fuzzy model and then a fuzzy decentralized state feedback controller is designed. A sufficient condition for stochastic stability of the NCS is obtained by using Lyapunov stability theory. This constructive sufficient condition is expressed as the LMI. Additionally, a numerical simulation example is exploited to verify the result of this chapter.(3) In the third part, we investigate the stochastic stability of a class of discrete-time NCS with uncertain network-induced time-delay and missing measurements via fuzzy decentralized control approach. We develop nonlinear systems by using the T-S fuzzy model and then a fuzzy decentralized state feedback controller with missing measurements is designed. A sufficient condition for stochastic stability of the NCS is obtained by using Lyapunov stability theory. The sufficient condition is expressed as the LMI. Finally, a numerical simulation example is provided to demonstrate the feasibility and effectiveness of the proposed method.