Filtering And Control For Dynamical Network Systems Under Event-Triggered Mechanism

Recently,the event-triggered mechanism has received an increasing research in-terest due to its advantage of improving the efficiency in resource utilization.On the other hand,as one of the main stream of research topics in control and signal processing,the filtering and control problems for dynamical network systems have received much research attention but also encountered some new problems,such as how to examine the effect from the event-triggered mechanism to system perfor-mance.This leads to the need of innovation in conventional filtering and control methods.Therefore,it has wide applications and more challenges to develop some novel event-triggered filtering and control strategies for dynamical network systems.In this thesis,the filtering and control problems are discussed for several classes of dynamical network systems under event-triggered mechanism.The addressed sys-tems mainly cover complex networks,genetic regulatory networks,neural networks and sensor networks.The content of this thesis can be divided into two parts.In the first part,we focus on the event-triggered filtering and control problems for some kinds of dynamical network systems subject to quantization effects,sensor satura-tions and randomly occurring delays.Based on the Lyapunov theory and matrix inequality techniques,some novel filter and controller design schemes are developed.In the second part,a dynamic event-triggered approach is proposed to deal with some issues of complex networks and sensor networks,and the desired synchroniza-tion controllers and distributed filters are designed.The compendious frame and description of the thesis are given as follows.·In Chapter 1,the research background and motivation are discussed,the outline and contribution of the thesis are introduced,and the research problems to be addressed in each individual chapters are also outlined.·In Chapter 2,we investigate the event-triggered H_?state estimation problem for a class of genetic regulatory networks with Markovian jumping parameters and time-varying delays.The purpose of the problem is to design the state estimators such that the estimation error system is stochastically stable with the H_?disturbance attenuation level.·In Chapter 3,the event-triggered H_?state estimation problem is considered for class of neural networks with sensor saturations and mixed delays.For each sensor,an event-triggered mechanism is employed to improve the efficiency in resource utilization.Then,by using the matrix analysis,the desired estimator parameters can be obtained.·Chapter 4 deals with the event-triggered H_?state estimation problem for a class of complex networks subject to state saturations,quantization effects as well as randomly occurring distributed delays.The desired estimator parameters are solved via solving a set of matrix inequalities.·In Chapter 5,the event-triggered distributed H_?state estimation problem is addressed for a class of state-saturated systems with randomly occurring mixed delays and then the desired distributed estimators are designed.Moreover,the ampled-data distributed H_?resilient state estimation problem is considered or nonlinear time-delay systems over sensor networks.By using the input delay approach,both the stability and H_?performance are analyzed for the estimation error system and a set of sampled-data distributed estimators is designed.·In Chapter 6,the event-triggered synchronization control problem is investi-gated for a class of complex networks with uncertain inner couplings.Based on the Lyapunov theory,a sufficient condition is derived such that the com-plex networks are synchronized and then the synchronization controllers are designed by solving a linear matrix inequality.·Chapter 7 is concerned with the synchronization control problem for a class of delayed complex networks under dynamic event-triggered mechanism and a set of controllers is designed such that the complex networks achieves exponentially ultimately bounded synchronization.In this chapter,a novel dynamic event-triggering strategy is introduced into the design of synchronization controllers for complex networks.·In Chapter 8,the distributed recursive filtering problem is studied for a class f discrete time-varying system under a dynamic event-triggered mechanism. ith the aid of inductive method,an upper bound on the filtering error covariance is derived which is subsequently minimized by properly designing the ilter gains at each sampling instant.·Chapter 9 summarizes the results of the the thesis and discusses some future work to be further investigated.