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Preliminary Study On Modeling, Control And Scheduling Of Multi-variable Networked Control Systems

Posted on:2010-10-21Degree:DoctorType:Dissertation
Country:ChinaCandidate:L S WeiFull Text:PDF
GTID:1118360278476288Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
With the fast development of computer technology, communication technology, network technology and control theory etc, the networked control technology and the networked control systems constructed upon network platform had been a hot research issue in the field of automation technology since the 1990s of the 20th century. It not only in practice can provide new ideas and methods to solve a lot of technical problems which had met or will meet in the remote real-time control systems, but also in theory can promote mutual infiltration and cross development of automatic control technology, computer technology and communication technology etc. Therefore the research of NCSs for our national industry, agriculture, military and civil is of great theory and application values.In this dissertation, these issues about modeling, control and scheduling of multi-variable networked control systems, which is increasing in the industry, are deeply studied. The complete continuous-time model, discrete-time model and multi-sample-time model are derived. The loose conservative sufficient conditions for convergence and robustness are given based on the research of time-delay systems theory, linear matrix inequality and free-weighting matrix method. And some new control methods are presented to perfectly solve the uncertainties problem about multi-variable networked control systems, such as dynamic feedback adaptive grey prediction scheduler, robust H∞controller, robust fault-tolerant controller and non-linear iterative learning tracking controller. At last, the local area network control systems of parallel coupled inverted pendulum are constructed to show the efficacy and feasibility of the proposed methods. The main research work is described as follows:1) The modeling of multi-variable networked control systems is presented. Based on the detailed analysis of networked control systems, the continuous-time differential mathematical model with multi-delay of networked control systems is described. Then using discrete-time system theory, the discrete-time mathematical model of networked control systems is proposed when the sensor node and controller node is time triggered, actuator is event triggered. At last the extended multi-sample-time mathematical model with short time-delay of multi-variable networked control systems is given by using lifting technology. It provides the basis for multi-sample-time networked control systems research.2)The issue of stability and robustness analysis for multi-variable networked control systems is researched under the condition of multi-packet transfer or single-packet transfer. Considering the correlation of the system states and the uncertainty of the system parameters, a new extended function of Lyapunov-Krasovskii is constructed. Then the delay-dependent sufficient conditions and the delay-independent sufficient conditions for systems are derived by using linear matrix inequality theory and free-weighting matrix method. Based on the above research, the more loose stability theorem and robustness theorem is given. The efficacy and feasibility of the proposed theory is shown by presenting simulation results.3) The robust controller and the adaptive grey predictive controller are designed. By using free-weighting matrix method, the simple and loose linear matrix inequality's condition for robust asymptotic stability is derived. The robust H∞controller and the robust fault-tolerant controller for uncertain continuous-time multi-variable networked control systems with actuators failure is designed based on the research of H∞control theory, where its network transmission is connected with network-induced delay and packet dropout. Then using grey theory and adaptive switching method, a new adaptive grey prediction control strategy for multi-variable networked control systems is proposed to reduce the effects of the system uncertainties. The whole modeling procedure of this method is established. The equal dimension GM (1,1) model is established by using metabolic principle. This method only identifies two parameters, and avoids online solving the Diophantine equation and inverse matrix. So the computation load of the algorithm can be reduced greatly, and real-time property is advanced.4) The stability and the iterative learning control approach for nonlinear multi-variable networked control systems are studied. By using the time-delay theory and linear matrix inequality method, the asymptotic stability conditions are derived for a class of general nonlinear plant with uncertainty. The tracking control method of iterative learning control for networked control systems is designed, which can track the desired trajectory for any arbitrary precision in a fixed finite interval. The tracking error of this approach tends to be zero as the number of iteration increases. And the convergence in the iteration domain can also be ensured.5) The issue of dynamic feedback scheduling strategy for multi-variable networked control systems is studied. A discrete time-variant mathematic model integrating control and information scheduling for multi-variable networked control systems is developed based on the research of the communication sequence notion and mixed logical dynamical framework. And the posedness conditions which can make system stable are derived too. Then using feedback scheduling ideas, the adaptive grey prediction dynamic feedback scheduling strategy is proposed. By on-line adjusting sample periods of the control systems sharing network resource, more network resources and higher priority is set for the control loop with poor performance. Then the network bandwidth are allocate to each control system dynamically so as to adapt to the variation of network load. The proposed algorithm can deal effectively with the dynamic network environment to overcome the shortcoming of traditional rate monotonic and reduce the network-induced delay, and can successfully give a solution to the problem of scheduling and control co-design.6) The novel multi-variable networked control systems experiment platform based on local area network is designed. The complete hardware and software design program of parallel coupled inverted pendulum is deeply researched. Then using adaptive grey prediction control and optimal control based model, the tracking control of campus network based distributed two inverted pendulum system and the stability control of campus network based parallel coupled inverted pendulum are realized on the developed networked control systems platform respectively. This platform can serves as a useful tool for theoretical researchers on multi-variable networked control systems. In conclusion, all the research work in this dissertation further expands the scope of plant in the application networked control systems, and provides the experimental foundation and the theoretical support for networked control systems promotion.
Keywords/Search Tags:Networked Control Systems (NCSs), Network-Induced Delay, Data Packet Dropout, Scheduling, Grey Prediction Theory, Grey Model (GM), H_∞Performance, Linear Matrix Inequalities (LMI), Iterative Learning Control (ILC), Parallel Double Inverted Pendulum
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