Analysis And Synthesis Of Networked Control Systems

Networked control systems(NCSs) are feedback control loops closed through a realtime network. Compared with conventional point-to-point control systems, NCSs havemany attractive advantages, such as low cost, resource sharing, simple installation，andeasy maintenance and so on. On the other hand, the introduction of networks alsopresents some challenging problem such as quantization, packet dropout andmultiple-packet transmission and so on, which bring difficulties for analysis and designof NCSs.In this dissertation, In terms of the Lyapunov approach and linear matrixinequality(LMI) techniques, the research of NCSs with network-induced delay, packeddropout, communication constraint, and variable-period sampling are studied. The maincontents are as follows:1. The quantized state feedback control problem for a class of networked controlsystem under variable-period sampling is studied. A new model with time-varyingsampling period and quantization signal is presented. By Lyapunov stability theory andlinear matrix inequality techniques, a quantized state feedback controller is designed fora class of networked control system under variable-period sampling, under the action ofthe controller, the closed loop system is exponentially mean-square stabilization.2. Analysis and control for a class of nonlinear networked control systems undervariable-period is addressed. Firstly, the problem of non-fragile guaranteed cost controlfor a class of nonlinear networked control systems with random delay and controllergain disturbance is considered. Based on variable-period sampling approach, thenetworked control systems are modeled as a nonlinear Markov jump systems. Under theaction of the non-fragile state feedback controller which is designed by means of theLyapunov method, the closed-loop system is stochastic asymptotically stable and itscost function value less than the specified upper bound. Secondly, the problem of robuststabilization for a class of networked control systems with random delay and nonlinearperturbation is considered. Applying variable-period sampling method, thediscretization of networked control systems is modeled as a nonlinear Markovian jumpsystems with partly unknown transition probabilities. The stochastic stability of theclosed-loop system is proved via Lyapunov stability theory, and at the same timemaximizes the bound on the non-linearity.3. The problem of model predictive control is proposed for networked control systems under variable-period sampling. Applying variable-period sampling method,the networked control systems is discretized and modeled as a Markovian jump linearsystems with partly unknown transition probabilities. Firstly, for a class of networkedcontrol systems with random delay and input constraints, using the linear matrixinequality method, the sufficient conditions are presented to guarantee asymptoticalstability and an upper bound of the receding horizon performance index of the closedloop system, and the design method of the predictive controller is also derived.Secondly, for a class of networked control systems with random delay and disturbances,the H predictive controller is designed based on the online method based on themin-max performance index.4. Analysis and control for a class of networked control systems with limitedcommunication channels is addressed. Firstly, the problem of control for a class ofnetworked control systems with limited communication channels and time-varyingdelay is considered. A new model is proposed to describe the discrete-time networkedcontrol systems with both limited communication channels and time-varying delay. Bychoosing appropriate Lyapunov function, the state feedback controller is designed byusing the discrete Jenson ineauality. Secondly, the problem of the stabilization for aclass of nonlinear networked control systems with limited communication channels anduncertain random delay is investigated. A novel control law model is proposed to takethe limited communication channels and uncertain random delay into considerationsimultaneously. By constructing the new stochastic Lyapunov function, a sufficientcondition is presented which guarantees the stochastic stability of the closed-loopsystems and at the same time maximizes the nonlinear bound.5. The problem of dynamic output feedback control is investigated for a class ofnonlinear networked control systems with both random packet dropout and randomdelay. Random packet dropout and random delay are modeled as two independentrandom variables. An observer-based dynamic output feedback controller is designed. Asufficient condition is presented for the stochastic stabilization of the closed systems.The quantitative relationship between the dropout rate, transition probability matrix andnonlinear level is derived by solving a set of linear matrix inequalities.