Networked control systems(NCSs)in recent years have received a wide range of considerations for theirs remarkable features in lower cost,higher reliability,higher flexibility,and easy maintenance,as opposed to traditional point-to-point control systems.But unfortunately it has also contributed to some problems not happened in the past,which mainly includes networkinduced delay and packet disordering.It is well known that the presence of these two problems in control loops can significantly degrade the performance of systems or even can bring about instability.On the other hand,descriptor systems provide a modeling method with a much wider inclusive range,when compared with standard state-space systems.That is because descriptor systems can take differential equation and algebraic equation in consideration at the same time.In addition,The Takagi-Sugeno(T-S)fuzzy systems is regarded as a very effective measure for modeling nonlinear systems arising in practice,which shows rather brief expressions in math and control theories.Therefore,under the framework of T-S fuzzy descriptor systems,this thesis deals with the problems of network-induced delay and packet disordering when system components are communicated through network.In order to lower effectively the negative influence from the two mentioned problems on the stability of system state,a method of fuzzy DDPU module(network-induced delay and packet disordering processing unit)is proposed to achieve this goal.The structure of fuzzy DDPU module could be divided into three steps generally.Firstly,two fuzzy premise variables are adopted into this module.Fuzzy premise variable ?1(t)is defined as the length of kth packet's network-induced delay which is ranked according to packets sort in the actuator.It is believed that the variation of ?1(t)can show the different delay lengths of different packets.In addition,fuzzy premise variable ?2(t)is defined as the difference of kth and k-1th packets' sampling instant,which could indicate whether a received packet is disordering or not,as well as its disordering degree.Secondly,based on the two fuzzy premise variables,we can associate two fuzzy set BIG and SMALL to ?1(t)at the same time,while associate two fuzzy set POSITIVE and NEGATIVE to ?2(t).Lastly,four IF-THEN fuzzy rules can be deduced based on the mentioned two steps.Every local fuzzy rule involves a additional parameter matrix Gi,which is used to regular the received control signal u(t).It is seen that the output of this fuzzy module will variate as the a received packet's network conditions including network-induced delay and packet disordering.In the background of networked control for T-S fuzzy descriptor systems,the type of Lyapunov functional has its particularity,which is mainly as the result of the time-varying input delay d(t).According to the definition of time-varying input delay in NCSs satisfying d(t)=t-sk,where sk is the sampling instant of kth packet,its derivative is the equation d(t)=1.However,when the equation is in the framework of descriptor systems,the particular complexity of admissibility problem in descriptor systems makes it inappropriate to use traditional Lyapunov functional.So a new kind of Lyapunov functional is constructed appropriately in this thesis.Based on this,the admissibility analysis and controller design to T-S fuzzy descriptor systems with time-varying input delay could proceed further.Finally,two examples of practical physical systems are presented in this thesis.The first one is modeled as T-S fuzzy descriptor systems controlled by network.This example is used to illustrate the basic process of using the fuzzy DDPU model to deal with network-induced delay and packet disordering.By this,the stable state responses of T-S fuzzy descriptor systems are presented by several figures.Moreover,the second example of flexible-joint robot arm system is modeled as T-S fuzzy state-space systems controlled by network.This is a example used to compare the fuzzy DDPU model method with tactics appearing in a known literature.The results show that the method of fuzzy DDPU model is better,not so much in achieving a much bigger maximum allowable upper bound,but more that it can stabilize system states much faster when compared with the tactic of selecting newest packet. |