Sampleddata Control For Two Classes Of Continuoustime Systems Under Different Sampling Schemes  Posted on:20121128  Degree:Master  Type:Thesis  Country:China  Candidate:X Fan  Full Text:PDF  GTID:2218330368989237  Subject:Pattern Recognition and Intelligent Systems  Abstract/Summary:  PDF Full Text Request  Recently, with the rapid development of digital measurement technology and intelligent instrument, many control systems consist of continuoustime plants and discretetime controllers (which can be implemented by digital computer, etc.), that is sampleddata control systems. In such systems, adopting different sampling schemes may affect the stability and performance of the systems directly. So it is a significant issue to investigate the sampleddata control for sampleddata control systems. On the other hand, many plants in industry have severe nonlinear characteristics. TS fuzzy models are shown to be universal function approximators in the sense that they are able to approximate any smooth nonlinear function to any degree of accuracy in any convex compact region. Hence, it is important to investigate the stochastic sampleddata control for nonlinear systems based on TS fuzzy models both in theory and practice.The main results in the dissertation are as follows.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, the problem of stochastic sampleddata control for a class of nonlinear continuoustime systems is investigated. For the sake of presentation simplicity, only two different sampling periods are considered whose occurrence probabilities are given constants and satisfy Bernoulli distribution, which can be further extended to the case with multiple stochastic sampling periods. By using the input delay approach and the TS fuzzy system method, a class of nonlinear continuous time systems with stochastic sampling is transformed into a continuoustime TS fuzzy system with timevarying delays and the stochastic parameters. Based on Lyapunov stability theory, a mean square asymptotic stability condition for the closedloop TS fuzzy system is proposed. Furthermore, the controller design method is given in terms of LMI. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.In chapter 3, the thesis investigates the exponential stabilization problem of linear systems under different sampling period of state subvectors. Since the sensors used for sampling different state variables are different and their sampling periods may be different, the state variables are reclassified in order that the controller uses the realtime sampling information and the state variables classified in the identical subvector are sampled by one same sampling period. Such sampling scheme is called the classifiedstates multirate sampling (CSMS) in this paper. By the input delay approach, the sampleddata control system with CSMS is modeled as a switched system with timevarying delays. Based on the switched system approach and Lyapunov stability theory, an exponential stability condition for such system is proposed, and the design of the corresponding switchedsampling controller is presented by solving a set of linear matrix inequalities (LMIs). Finally, to demonstrate the merits of the proposed approach, we compare it with the controller design method under single rate sampling of all state variables for the sampleddata control of the rotating base pendulum and closedloop automobile driving.In chapter 4, the main results of the thesis are concluded, and some research directions on sampleddata control in future are proposed.  Keywords/Search Tags:  TakagiSugeno (TS) fuzzy systems, Stochastic sampling, Mean square asymptotic stability, Linear systems, Classifiedstates multirate sampling (CSMS), Linear matrix inequality (LMI), Switched control systems  PDF Full Text Request  Related items 
 
