Performance Analysis And Synthesis For Several Classes Of Discretetime Stochastic Systems With NetworkEnhanced Complexities  Posted on:20150413  Degree:Doctor  Type:Dissertation  Country:China  Candidate:D R Ding  Full Text:PDF  GTID:1228330467450239  Subject:Control theory and control engineering  Abstract/Summary:  PDF Full Text Request  The thesis is concerned with the performance analysis and synthesis for several classes of discretetime stochastic systems with various networkenhanced complexities. The complexities under consideration mainly include fading measurements, randomly occurring deception attacks, eventtriggered communication mechanism, randomly occurring sensor saturations and randomly varying sensor delays. Then, the addressed systems cover general stochastic nonlinear systems and some timevarying discretetime stochastic systems such as stochastic parameters systems, statesaturated timevarying systems, sensor networks and multiagent systems. Furthermore, some novel concepts, models of networkenhanced complexities, performance criteria in probability are proposed to account for the realworld engineering requirements. They mainly involve the consensus in probability, the security in probability, the randomly occurring deception attacks, the discrete version of inputtostate stability in probability and the envelopeconstrained filtering performance.The content of the thesis can be divided into two parts. In the first part, the thesis focuses on finite horizon state estimation and control issues with networkenhanced complexities for discrete timevarying stochastic systems. Some new controller and estimator design schemes are developed in terms of the solutions to recursive matrix inequalities (RMIs) or backward recursive Riccati difference equations (RDEs). In the second part, the inputtostate stability in probability (ISSiP) is established for a general discretetime stochastic nonlinear system. According to such a theory, the eventtriggered consensus control and the security control are, respectively, investigated for stochastic multiagent systems and discretetime stochastic nonlinear systems. Some sufficient conditions are established to guarantee the prescribed performance requirements and obtain the desired controller parameters. In addition, the state estimation problem is discussed for a class of general discretetime complex networks with randomly occurring sensor saturations (ROSSs) and randomly varying sensor delays (RVSDs). The estimator parameters are solved easily by using the semidefinite programming method. The compendious frame and description of the thesis are given as follows.First, the finitehorizon H∞control problem is investigated for discrete timevarying nonlinear systems with simultaneous presence of fading measurements and randomly occurring nonlinearities. For the desired H∞performance, an auxiliary index is constructed and then a necessary and sufficient condition is derived to guar antee such an auxiliary index. Furthermore, a novel H∞control scheme is proposed by utilizing model transformation techniques combined with a certain H2type criterion. According to such a framework, the H∞consensus control problem for discrete timevarying multiagent systems with both missing measurements and parameter uncertainties, and the distributed H∞state estimation problem for discrete timevarying nonlinear systems with both stochastic parameters and stochastic nonlinearities are discussed, respectively. For stochastic parameter systems, a necessary and sufficient condition is established to achieve the H∞performance constraint. Furthermore, the desired distributed controller/estimator parameters are characterized via solving coupled backward recursive RDEs.Second, a critical theoretical framework is established for analyzing the socalled inputtostate stability in probability (ISSiP) for general discretetime nonlinear stochastic systems. Based on such a framework, the eventtriggered consensus control issue is investigated for a class of discretetime stochastic multiagent systems with statedependent noises. A novel definition of consensus in probability is proposed to better describe the dynamics of the consensus process of the addressed stochastic multiagent systems, and an eventtriggered communication mechanism is adopted with hope to reduce the communication burden and the energy consumption. By using the matrix analysis, a novel codesign scheme about the control gain and the threshold in the eventtriggered control protocol is proposed to achieve the desired consensus in probability. Furthermore, the security control problem is addressed for discretetime stochastic nonlinear systems. In the systems under consideration, a novel phenomenon, namely, the randomly occurring deception attack, is firstly taken into investigation. Attention is focused on the design of a dynamic output feedback controller such that the desired security is guaranteed and an upper bound of the given quadratic cost criterion is obtained. By utilizing the ISSiP approach, some sufficient conditions are established for the existence of the desired controller in virtue of the solvability of a set of matrix inequalities.Third, the dissipative control problem is considered for a class of discrete timevarying systems with simultaneous presence of state saturations, randomly occurring nonlinearities as well as multiple missing measurements. A new controller design algorithm is provided such that the desired dissipative performance requirement of the closedloop systems can be guaranteed via introducing a free matrix with its infinity norm less than or equal to1. Furthermore, by utilizing the similar line in the dissipative control problem, the H∞filtering problem is addressed for discrete timevarying systems with state saturations, randomly occurring nonlinearities as well as successive packet dropouts. The desired filter parameters can be characterized via solving recursive matrix inequalities.Finally, the envelopeconstrained H∞filtering problem is investigated for a class of discrete timevarying stochastic systems with fading measurements and randomly occurring nonlinearities. A novel envelopeconstrained performance criterion is proposed to better quantify the transient dynamics of the filtering error process over the finite horizon. By utilizing the ellipsoid description on the estimation errors, the desired filter gains are characterized via solving recursive matrix inequalities (RMIs). On the other hand, a novel sensor model is proposed to describe randomly occurring sensor saturations (ROSSs) and randomly varying sensor delays (RVSDs) within a unified framework via two sets of Bernoulli distributed white sequences with known conditional probabilities. Furthermore, in light of such a measurement model, the H∞state estimation problem is discussed for a class of discrete timedelay nonlinear complex networks. The desired estimator parameters are characterized via solving a convex optimization problem.  Keywords/Search Tags:  Networkenhanced complexities, discrete timevarying systems, general discretetime stochastic nonlinear systems, sensor networks, multiagent systems, finitehorizon, distributed state estimation, consensus, security  PDF Full Text Request  Related items 
 
