Control And Scheduling Of Networked Control Systems

The methods of control and scheduling for networked control systems (NCSs) arestudied in this dissertation. The main research works are concluded as follows:(1) The compensation and control methods for linear networked control systems arestudied. Firstly, the NCS existing uncertain short delay and data packets dropout is concerned.A dropout compensator is designed to predict state when data packet is dropout. The NCS canbe equivalent to a discrete switched system with parametrical uncertainties. Then based on themodel, the design method of state feedback controller and compensator is given by using theapproaches of Lyapunov and Linear Matrix Inequality (LMI). Secondly, considering the NCSwith time-vary long delay and data packet dropout, an observer composed by open-loopprediction and close-loop prediction is proposed to compensate the effect of delay and datapacket dropout. Based on separation principle, the methods of controller design and obserberdesign are given respectively.(2) A dynamic scheduler for NCS is studied. By on-line adjusting sample periods ofthe control systems sharing network resource, the network bandwidth are allocate to eachcontrol system dynamically so as to adapt to the variation of network load. The dynamicscheduler is composed of network state monitor, prediction algorithm and sample periodadjusting rule. The monitor samples the network state with equivalent interval, then thepredict algorithm predicts the network utilization and data packets execution times by usingthe current network state acquired by the monitor. For different demands of system utilization,the prediction algorithms of network utilization are different. For those NCSs given utilizationsetting value, the prediction algorithm is designed based on feedback control mechanism. Forthe NCSs without utilization setting value, a AR model is established to predict the networkutilization. Both NCSs are using AR model to predict data packets execution times. Based onthe predictive values of network utilization and data packets execution times, sample periodsadjusting rule allocates network resource and computes the new sample periods according tothe network-induced error and control error. The effectiveness and priorities of dynamicscheduler we proposed are validated by a group of simulation.(3) The methods of control and scheduling co-design for NCSs are discussed. TheNCS scheduled by the above dynamic scheduler is a vary-period system. Firstly, consideringthe ideal scheduling situation under which delay and data packet dropout can be ignored, theNCS is equivalent to a class of discrete time system with parametrical uncertainties bymathematical transformation and matrix theory. Then a design method of state feedback controller is studied by using the approaches of Lyapunov and LMI. Furthermore, the NCSunder non-ideal scheduling is considered. It is assumed that uncertain short delay and datapacket dropout occurred in the network, then the NCS is modeled as a discrete time switchedsystem with parametrical uncertainties. With the theory of switched systems control and LMIapproach, a state feedback controller is designed to stabilize the NCS. So, the control andscheduling can be co-designed based on the methods of modeling and control for vary-periodsystems we proposed.(4) The modeling and control approaches for nonlinear NCSs are studied. Thecontrol methods for the NCSs which plant can be described by T-S fuzzy models are studied.Considering the effect of uncertain short delay, the NCS is modeled as a discrete time T-Sfuzzy model. With the theory of fuzzy control and LMI, a method of fuzzy state feedbackcontroller is given. Then the H_∞controller method is also studied. A fuzzy controller isdesigned to guarantee the system stability as well as satisfying the H_∞performance index.