Research On Event-triggered Control For Networked Control Systems

With the development of science and technology,the scale,structure and complexity of modern industrial system are increasing.The traditional point-to-point structure cannot meet new demands of modern production,such as low cost,easy installation,space resource constraints,good flexibility.By connecting the sensors,controllers,actuators and other components of the controlled system through the network,it can accommodate larger control systems,achieve longer distance control,and accomplish more control objectives.Because of the advantages of simple installation and maintenance,high flexibility and reliability,and resource sharing,networked control systems have been widely used in mobile robots,industrial production processes,urban transportation,aerospace and other fields.Meanwhile,the introduction of the network has also brought new challenges to analysis and design of control systems.The networked control systems have high requirements on the bandwidth and transmission frequency of the signal transmission channel.When the communication network has limited bandwidth and frequent signal interaction,network-induced delay and packet loss may occur,which may affect the actual operation of the control system performance.How to reduce the amount of signal transmission and save network resources effectively while ensuring system performance has been one of the hot issues in recent years.The emergence of event-triggered control provides an important technique to reduce the frequency of signal transmission and the burden of communication network.Based on the previous results,this dissertation is concerned with event-triggered control for linear networked control systems.Combined Lyapunov stability theory with linear matrix inequality(LMI)technology,the conditions for co-design of event-triggered mechanism and controller are obtained.The main results are proved theoretically,and the effectiveness of the proposed theoretical methods are verified by simulation examples.The main contents are outlined as follows:Chapters 1-2 systematically analyze and summarize the background and development of the networked control systems as well as the event-triggered control.Preliminaries about the considered problem are also given.Chapter 3 considers the event-triggered state feedback control problem for networked control systems with input saturation.First,a method for estimating the domain of attraction of the origin for a system is presented in the absence of external disturbances.Then,this approach is extended to the systems with external disturbances,and an optimization method based on LMI is developed for designing the event-triggered mechanism and the state feedback controller that achieve disturbance rejection with guaranteed stability requirements.Finally,simulation examples are given to demonstrate the superiority of the proposed method.Chapter 4 investigates the problem of event-triggered non-fragile dynamic output feedback controller design for linear systems with actuator saturation and disturbances.The controller to be designed is supposed to include additive gain variations.By using Lyapunov stability theory and adding slack matrix variables,new sufficient conditions are derived to design the event-triggered parameters and the controller gains.Compared with the existing non-fragile dynamic output feedback controller design methods,the structural restriction on the Lyapunov matrix is relaxed.The effectiveness of the proposed method is demonstrated by two examples.Chapter 5 focuses on the event-triggered dynamic output feedback control for networked control systems subject to communication delays.The control input and the measurement output can be transmitted asynchronously based on two independent event generators.As a result,communication resources can be further saved.Under the proposed framework,the closed-loop system is modeled as a switched system with a time-delay,based on which a novel exponential stability criterion is derived.This criterion is of less conservatism due to that the chosen Lyapunov-Krasovskii functional is not necessarily decreased.Moreover,the control gains and event-triggered parameters can be co-designed if the related linear matrix inequalities are feasible.The effectiveness of the proposed method is demonstrated via two numerical examples.Chapter 6 presents a novel dynamic event-triggered control scheme for linear timeinvariant systems.First,a dynamic event-triggered mechanism is developed by introducing an additional dynamic variable.The projection technique is adopted to restrict the additional variable to a given interval.Based on this event-triggered mechanism,an event-based state feedback controller is designed.Then,a new Lyapunov-Krasovskii functional is constructed to reduce conservatism,which takes the sampled data into consideration.The stability criteria are derived with the help of the mathematical induction and Lyapunov theorem.In addition,the controller gain and weighting matrices in the event-triggered mechanism can be obtained simultaneously.Compared with the existing results for static strategies,the proposed dynamic strategy is more flexible and generates fewer events.Finally,simulation examples are provided to demonstrate the effectiveness of this new scheme.Chapter 7 investigates the event-based leader-following consensus for linear multiagent systems under a directed communication topology.A novel dynamic eventtriggered mechanism is put forward to schedule the inter-agent communication.Different from the existing event-triggered mechanisms,the proposed mechanism involves internal dynamic variables that play an important role in excluding Zeno behavior.Then,an event-based distributed control protocol is developed by using locally triggering data.It is proven that the leader-following consensus is achieved under our control strategy.Moreover,the criterion for designing a desired triggered mechanism and control protocol is derived in terms of linear matrix inequalities.Numerical simulations demonstrate that the proposed strategy is capable of reducing communication more effectively than the existing results.Chapter 8 summarizes the results of the dissertation and points out the future research topics.