Research On Output Feedback Predictive Control Of Networked System Based On Adaptive Event-triggered Mechanism

In the past ten years,networked control has been one of the hot research directions in academia,among which packet loss and network security issues have received the most attention.Aiming to solve the problems of packet loss and cyber attack in networked systems,this thesis systematically studied the synthesis approaches of dynamic output feedback model predictive control for nonlinear networked systems,by using Lyapunov stability theory,quadratic bounded method and linear matrix inequality(LMI)technology as the basic tools and by adopting the research idea of time-triggered mode,then event-triggered mode,and finally adaptive event-triggered mode according to the development of the triggered mode of networked system.The main contents of this thesis include the following three aspects:1.The dynamic output feedback guaranteed cost control method for nonlinear networked systems with packet loss and bounded disturbance is studied.Firstly,the interval type-2(IT2)Takagi-Sugeno(T-S)fuzzy model is used to describe the nonlinear system and the stochastic variables satisfying Bernoulli distribution are introduced to characterize the process of packet loss.Then,the quadratic bounded technique is used to describe the closed-loop stability of nonlinear networked systems under bounded disturbance.Finally,the existence conditions and design methods of the dynamic output feedback guaranteed cost controller are given,and a controller that can guarantee the robust stability of the closed-loop system and meet the corresponding performance index within a given upper bound is obtained.2.For the nonlinear networked systems with packet loss and deception attack,the synthesis approach of multi-step dynamic output feedback model predictive control based on event-triggered mode is studied.Firstly,in order to save communication resources,an event-triggered condition that can determine whether to send the current packet is designed.Secondly,two stochastic variables satisfying Bernoulli distribution are introduced to describe the model of random packet loss and deception attack.Thirdly,by optimizing a series of feedback laws within a given period of time,a multi-step parameter-dependent dynamic output feedback model predictive controller is obtained.Finally,to improve the control performance,an auxiliary optimization problem that can reduce the estimation error bound is designed.3.For the nonlinear networked systems with bounded disturbance and denial of service attack,the synthesis approach of dynamic output feedback model predictive control based on adaptive event-triggered mode is studied.Firstly,in order to reduce the conservativeness of the event-triggered mode,an adaptive event-triggered condition that dynamically adjusts the triggered threshold according to system changes is designed.Then,by introducing the free estimation state,the synthesis approach of dynamic output feedback model predictive control with a free control move is constructed.Finally,the recursive feasibility of the model predictive control optimization problem and the stability of the closed-loop system are proved.