Predictive And Optimum Control Of Cyber Physical Systems Under Network Stochastic Constraints

The emergence of Cyber Physical System(CPS)has realized the mapping,interaction,and collaborative optimization of key elements in information space and physical space,which also reflects the trend of control systems becoming more intensive,efficient and intelligent.In particular,it is widely used in various industries because of its many advantages such as low cost,easy maintenance,security and efficiency.However,with the introduced of open networks,the network communication problems of CPS have been the main factors affecting its overall performance.For many problems such as random packets loss,limited network resources and external disturbances,we use various methods such as switching system approach,model predictive control,optimal control theory and event-triggered control for system modeling and controller design from a perspective of control theory.This thesis consists of three main parts as follows:(1)A model-based control method is used to address the random data packets loss that occurs during network communication.Firstly,we describe the network packets loss problem by Markov model and design the corresponding states feedback controller.Secondly,the LyapunovKrasovskii stability judgment method is used to analyze exponential stability conditions which are required to guarantee stability of the system.Finally,we obtain corresponding control algorithm by linear matrix inequality method,and verify effectiveness of designed control algorithm by inverted pendulum trolley control experiment.(2)Based on modeling and analysis of the random packets loss,the problem of limited system bandwidth resources is considered comprehensively.Firstly,by analyzing and comparing problems under study,Firstly,we use switching system theory to design a controller that combines event-triggered control with model predictive control.Secondly,the LyapunovKrasovskii method is used to solve sufficient conditions and exponential decay rates to ensurse stability of system.Finally,we demonstrate effectiveness of designed cooperative controller by a simulation example.The method we designed not only optimizes overall performance of systems,but also solved problems that multiple control methods are not easily designed together in a controller.(3)We analyze not only problems of random packets loss and limited network bandwidth resources,but also problems of system affected by external disturbance.For problems,we have designed a cooperative control strategy of event-triggered,predictive control and robust control,and proposed a optimal performance function to guarantee system performance.Especially,we transform control performance optimization problems into solving optimal value of cost functions using dynamic programming.Then,a designed controller is analyzed based on stability theory,and effectiveness of our controller is verified by using intelligent cart trajectory tracking experiments.More importantly,we proposed some perspectives on translation of designed control algorithms from theory to practical applications.