Research On Quantized Filtering And Tracking Control Of Networked Nonlinear Systems

In recent years,the study of networked systems has attracted much attention from scholars at home and abroad in the control area.In contrast with the conventional point-to-point control systems,networked systems have many advantages such as less wiring,high reliability,low cost,ease of expand,maintenance,and installation,etc.Due to these benefits,networked systems have found applications in a wide range of areas such as industrial automation,unmanned vehicles,smart grids,and so on.In networked systems,due to the limited bandwidth of communication network for information exchange,the singals should be quantized before being transmitted.This is mainly due to that quantization is one of most important techniques in decreasing the signal transmission burden of communication channels.In addition,transmission delay,packet loss,and data disorder caused by network congestion can be effectively avoid via quantization.Therefore,quantization effects are unavoidable in networked systems,and the study of quantized control issues for networked systems is both theoretically and practically important.Based on previous works of others,this thesis further investigates the problems of quantized filtering and tracking control for networked nonlinear systems,and the main contributions of this thesis are summarized as follows:1)The energy-to-peak filtering problem of networked nonlinear systems with the effects of dynamic quantization is addressed based on T-S fuzzy model approach.A novel quantized filtering strategy is proposed for T-S fuzzy systems.Both the full-order and reduced-order quantized energy-to-peak filters design problems for T-S fuzzy systems are solved in the framework of linear matrix inequality.The developed quantized filtering strategy is a one-step approach,that is,the filter and the quantizer's dynamic parameter can be obtained synchronously.Compared with the existing results,the developed quantized filtering strategy is effective for T-S fuzzy systems and energy-to-peak filtering problem.2)The problem of robust energy-to-peak filtering for uncertain Lipschitz networked nonlinear systems with the effects of static quantization is investigated.The uncertainty coupling terms of the system uncertainties and quantization errors will be eliminated by using the two-step approach.Consider different order for eliminating the two types of uncertainties,two sufficient conditions for the design of the quantized robust energy-to-peak filter are given in the form of linear matrix inequalities.3)The non-fragile H_?tracking control problem of networked nonlinear systems with input and output dynamic quantization effects is studied based on T-S fuzzy model approach.A novel quantized tracking control strategy is proposed for T-S fuzzy systems.The quantized non-fragile H_?tracking controller design problem for T-S fuzzy systems is solved in the framework of linear matrix inequality.The developed quantized tracking control strategy is a one-step approach,that is,the non-fragile H_?tracking controller and the quantizers'dynamic parameters can be obtained synchronously.Compared with the existing results,the restriction on the lower bound of the quantizers'ranges and the necessary scaling relation between two quantizers'parameters are avoided.4)The problem of dissipative tracking control is addressed for networked nonlinear systems with input and output static quantization effects based on T-S fuzzy model approach.Different from the existing results,the quantization effects have been considered in the communication channels from the plant and the reference model to the controller and from the controller to the plant rather than the case that only quantized measurement output or quantized control input was considered.By using the descriptor representation approach and the free-weighting matrix approach,the quantized dissipative tracking controller design problem for T-S fuzzy systems is solved in the framework of linear matrix inequality,which is more general than the conventional quantized H_?tracking controller design problem.5)The event-triggered H_?tracking control problem is researched for networked nonlinear systems with input and output static quantization effects based on T-S fuzzy model approach.A novel asynchronous event-triggered communication scheme is given to reduce the network communication burdens in both communication channels from the plant to the controller and from the reference model to the controller.By using the two-step approach and the matrix inequality decoupling approach,the asynchronous event-triggered H_?tracking controller design problem for T-S fuzzy systems with the effects of static quantization in both communication channels from the plant and the reference model to the controller and from the controller to the plant is solved in the framework of linear matrix inequality,which is more general than the synchronous event-triggered H_?tracking controller design problem.Finally,the results of the dissertation are summarized and further research topics are pointed out.