Research On Predictive Control Of Networked Control System Under Complex Environment

Control systems that form feedback through the network are called network control systems(NCSs).Compared with the traditional control system,the NCSs have the advantages of low cost,convenient system integration,simple installation and maintenance,substantial flexibility,high reliability,etc.However,data transmission over the network will encounter some inevitable problems,which will bring a series of issues never experienced in traditional control systems,such as network-induced delay,data packet loss,packet disorder,etc.,collectively referred to as network constraints.Similarly,the system is also subject to internal and external disturbances,such as loss of measurement missing and sensor or actuator faults.In these complex environments,these factors can deteriorate the system or even make the system unstable.Therefore,dealing with network constraints and internal and external disturbances is a fundamental problem in studying the NCSs.In the study of the problems above,the method based on predictive control strategy(NPC)has become the most representative method because it makes full use of the characteristics of the NCSs,and its feasibility has been confirmed by theoretical analysis and physical experiments.However,this method is relatively fixed and single,basically dealing with linear systems,for systems with random signals cannot be processed temporarily,and the stability research is mostly infinite time domain for the study of finite time domain because it is affected by controller design difficulties,there is also a lack of adequate tool.Starting from effectively solving these problems and ensuring the reduction of the adverse effects caused by network constraints,this dissertation designs relevant predictive control strategies to realize and analyze them.Firstly,the problem of the networked predictive control systems(NPCs)with induced time delays and data packet dropouts is investigated,a new networked predictive control scheme is designed based on the designed observer and prediction strategy,and a model of NPCs is established.Second,an improved method of combining matrix singular value decomposition(SVD)with multivariate presupposition is proposed to handle different time delays and data packet dropouts.Then,sufficient new conditions are derived.Subsequently,the desired controller and observer gain matrices to be acquired,which can make the closed-loop system finite-time stable and finite-time boundedness.Finally,the network-induced delays and data packet dropouts are actively compensated.Secondly,the finite-time H∞ predictive control problem for stochastic networked control systems with communication constraints is studied.Firstly,absorbing the phenomena of unmeasurable state and missing measurements,the non-fragile observer(NFO)-based NPC strategy is obtained to compensate the time delays and packet dropouts.Different from the previous prediction strategy,a disturbance-based prediction mechanism is adopted.Based on it,a novel NPCs model is constructed,where the missing measurement is first considered in studying NPCs with time delays and packet dropouts.Sufficient conditions are derived to ensure the closed-loop systems’ stochastic finite-time boundedness with a prescribed H∞ performance.Subsequently,criteria for co-designing the uniform predictive controller and the non-fragile observer are designed based on the bounded time delays and packet dropouts.Thirdly,the problem of predictive control for a class of NCSs based on the cloud storage method(CSM)is discussed.A hybrid networked predictive control method is proposed to improve the system’s transient performance and actively compensate for the time-varying delays and data packet dropouts.Then,the switched control system is established based on switching signals varying with the time-varying delays and data packet dropouts.Novel finite-time hybrid stabilization controllers are proposed by using networked predictive control theory.Finally,sufficient conditions are developed to ensure the finite-time boundedness of the augmented switched systems.In the sequel,considering the mixed delays,the problem of finite-time control design for a class of NCSs is studied.First,a novel hybrid dropout compensation method is designed to reasonably use available system feedback information,which can actively compensate for data packet dropouts in two communication channels.Second,an improved augmented switched system model is constructed based on the mixed delays and the hybrid parameter.Then,the gain matrices that vary with the data packet dropout are formulated to ensure stochastic finite-time stability and improve the transient control performance of the resulting closed-loop system.The extended slack variables-based algorithm is presented to reduce the computation time,and the average dwell-time switching law is determined.Finally,a PID networked predictive control method is first proposed to improve the control performance.This method makes use of historical information and its error of prediction state.Furthermore,an augmented switched control system is established in which the time-varying delay determines the switching signal.Sufficient conditions are derived so that the resulting systems are finite-time boundedness.Then novel finite-time PID controllers and the corresponding finite-time observers are designed to compensate for the time-varying delays actively.