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Delay-dependent H_∞ Control For T-S Fuzzy Time Delay Systems And Its Application In NCS

Posted on:2009-05-07Degree:MasterType:Thesis
Country:ChinaCandidate:D W ZhangFull Text:PDF
GTID:2178360272963580Subject:Pattern Recognition and Intelligent Systems
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It is well known that nonlinear dynamics exist in most practical control systems.Considering the uncertainties of the controlled plants usually occurred in modeling and ever-present time-delay phenomenon,it is a significant issue to design a robust controller for uncertain nonlinear systems with time delay.On the other hand,networked control systems(NCSs) are feedback control systems with the control loop closed via a real-time network. In such NCSs,a controller and spatially distributed sensors/actuators are grouped into network notes respectively and communicate by exchanging packet-based messages through a network.Thus the NCSs share greater flexible structure,more powerful function and more complicated analysis and synthesis.The insertion of the communication network makes conventional control theories be reevaluated before they can be applied to NCSs.Hence,it is important to investigate the NCSs with nonlinear controlled plant,not only in theory but also in application.In chapter 1,the significance of this thesis is introduced in both theory and application.And the research situation at home and abroad is recalled.In chapter 2,an uncertain T-S fuzzy model is firstly adopted to represent nonlinear systems with time-varying delay,in which the modeling errors are absorbed in the uncertainty part.Then based on a novel Lyapunov-Krasovskii function,the delay-dependent robust H_∞control problem for T-S fuzzy time delay systems is considered.The design method of robust H_∞controller and new stabilization results are developed respectively in terms of LMIs,which are both less conservative than the existing ones.The efficiency of our design methods are finally illustrated by two numerical examples.In chapter 3,for a class of NNCSs which is composed of a nonlinear controlled plant,a reference model and network nodes,by the parallel distributed compensation(PDC) technique and choosing reasonable driven mode of network nodes,the tracking control model for such NNCSs is established and the synthetical network index with both network-induced delay and packet losses and a H_∞tracking performance index in the network environment are presented.Based on the situation above,resorted to the idea in chapter 2,the tracking control problem is considered by using the H_∞fuzzy tracking control approach.The efficiency of our design method is finally verified by simulation on a Duffing Forced-Oscillation system.In chapter 4,the main results of the thesis are concluded,and some research issues in future are proposed.The main contributions of the dissertation are as follows:(1) A novel Lyapunov-Krasovskii function is presented.And the design method of robust H_∞controller and new stabilization results for T-S fuzzy time delay systems are respectively established in terms of LMIs,which reduce the conservatism of the previous results.(2) Based on the T-S fuzzy model and the fuzzy PDC technique,the novel tracking control model for a class of NNCSs is firstly established,then the tracking control design for such NNCSs is equivalent to a feasibility problem of the provided criterion in terms of LMIs,which facilitates greatly network designers to resort our results in practice.(3) Considering the relation between the measured data of controlled plant and available data of the fuzzy controller via network transmission (includes premise variables),the difference of the fire mechanism between the T-S fuzzy model of the controlled plant and the fuzzy controller is revealed.(4) A synthetical network index with both network-induced delay and packet losses is presented,and the tracking control for a class of NNCSs based on T-S fuzzy model is firstly investigated.
Keywords/Search Tags:Robust H_∞control, T-S fuzzy model, Nonlinear networked control systems (NNCSs), Tracking control, Network-induced delay, Packet losses, Linear matrix inequality (LMI)
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