Event-triggered And Self-Triggered Control For Linear Switched Systems Under Network Environment

In recent years,switched system has been widely applied in modeling and research of power system,robot system,traffic system and other practical control systems.As a class of important hybrid systems,switched systems include a series of continuoustime or discrete-time subsystems and a rule which orchestrates the switches among them.On the other hand,with the development of networked control system,network congestion and bandwidth limitation occur inevitably.In such a case,event-triggered control emerges and it can largely reduce the occupation of bandwidth and save network resources.The related problems of event-triggered and self-triggered control for switched systems are investigated in this thesis.The main contents are listed below:First,for switched systems where the sensor and controller are not co-located,a dual channel asynchronous dynamic event-triggered mechanism is designed for the sensor-controller channel and the controller-actuator channel.At the same time,the dynamic output feedback controller is designed so that the closed-loop system can be asymptotically stable.Then,the corresponding self-triggered conditions are put forward.The simulation verification is carried out with the example of F-18 aircraft.Second,periodic event-triggered condition is designed for switched systems which are composed of both continuous-time and discrete-time subsystems.Based on the mode-dependent average dwell time,a criterion is presented to ensure the exponential stability of switched systems.Periodic event-triggered control,which combines the advantages of periodic control and event-triggered control,can avoid Zeno behavior.Finally,for switched systems with partial unstable subsystem,we design an event-triggered mechanism involving elementary time unit.This ensures the next triggering instant is followed by a unit of latest triggering instant.The sufficient conditions for the exponential stability of the system are given according to the time-scheduled Lyapunov function and the mode-dependent average dwell time approach.