Research On Networked Control Systems With Disturbance And Uncertainty And Application

Networked control systems(NCSs)are distributed feedback control systems,in which the system components,such as sensors,controllers,and actuators are elsewhere and connected through a wired/wireless communication network.Compared with traditional point-to-point control systems,NCSs have several advantages,such as resource sharing,low cost,easy extensibility,simple installation and maintenance and high reliability.However,with widespread application of NCSs,they also bring many chanllenging problems.On the one hand,some uncertain factors maybe occur during the process of network transmission,such as network-induced delay,packet dropouts,and packet disorder,etc.On the other hand,the controlled plant itself is inevitable affected by interference,main including: external input disturbance,sensor/actuator faults,network attack,etc.These challenging issues could cause instability of plant,and even worse,destroy the controlled plant.How to effective compensate the uncertain factors in NCSs.How to effective damp the disturbance and tolerate fault.How to effective defense the network attack.They are the common problems faced by the scientific community today,and they are also the key issues to be solved in this paper.In order to deal with the aforementioned issues,the correspondingly control algorithms are proposed.The effectiveness of designed methods are verified by combining the motor system,power system,intelligent vehicle system,and mass-spring-damping system in industrial control.The main research contents include the following five parts.1)The sliding mode tracking control problem of networked control systems with random delay and packet dropouts is studied.Considering the random delay and packet dropouts are existed in feedforward channel and feedback channel of networked DC permanent magnet synchronous motor system,a network compensation algorithm based on sliding mode control and pseudo partial derivative theory is proposed.First,the mathematical model of the DC motor is transformed into a dynamic data-driven model of the equivalent bias format.Secondly,a sliding mode tracking controller based on pseudo partial derivative theory is designed.Furthermore,in order to compensate for random delay and packet dropouts,a network predictive control algorithm based on sliding mode is designed.Finally,the effectiveness of the designed algorithm is verified by the networked DC motor simulation experiment.2)The problem of robust H? control for networked control systems with variable topologies is studied.For intelligent networked vehicle systems with coupling,in which,the vehicle and the vehicle through the vehicle network to achieve communication interaction,a stability analysis algorithm based on robust H? control is proposed.Firstly,a discrete-time state space model of intelligent networked vehicles is established.In this mathematical model,the dynamic topology of the vehicle network and the random network-induced delay are considered simultaneously.Secondly,considering the controller's coupling,two output feedback controllers are designed.In which,in order to achieve decoupling,a new output feedback coupling controller is designed.Furthermore,in order to guarantee the stochastic stability of the closed-loop intelligent network vehicle system,the delay-dependent stability condition based on Lyapunov theory is given.Finally,the effectiveness of the designed algorithm is verified by the intelligent networked vehicle simulation experiment.3)The problem of robust adaptive sliding mode control for switched networked control systems with sensor and actuator faults is studied.A new observer-based robust sliding mode control algorithm is designed for switched networked control systems with sensor and actuator faults.First,an observer is designed to estimate the state of the system and compensate for interference.Secondly,an observer-based second-order discrete-time adaptive sliding mode controller is proposed.In which,the second-order discrete-time adaptive sliding mode function based on the estimated state and the fault is designed.Different from the existence algorithm,the proposed adaptiveity of the second-order sliding mode function mainly depends on the estimation of the fault.Further,the designed robust sliding mode controller is used in the networked control system.In order to compensate for network-induced delay,packet dropouts and disordering,a network predictive control algorithm is designed.Finally,the effectiveness of the proposed algorithm is verified by a digital simulation example and a mechanical system simulation.4)The K-order sliding mode tracking control problem of networked control systems with communication constraints and external disturbances is studied.Considering the communication constraints and external disturbances are simultaneously existed in networked control systems,a network predictive control algorithm based on K-order adaptive discrete sliding mode control is proposed.Firstly,a K-order adaptive discrete sliding mode controller is designed to damp external disturbance.Secondly,in order to compensate the communication constraints,a new network predictive control algorithm is designed.Finally,the effectiveness of the designed algorithm is verified by the DC motor Servo system.The simulation results show that the designed control algorithm can effectively suppress external interference,compensate communication constraints,and achieve good tracking performance.5)The problem of robust sliding mode control in networked control systems with false data injection(FDI)attacks is studied.Considering interarea oscillations caused by FDI attacks in wide-area power systems.In order to defend against opponent attacks and damp out the interarea oscillations,a wide-area robust sliding mode control(WARSMC)algorithm is proposed.First,in order to estimate the state of the system and defend against actuator attacks,an extended state observer was designed.Secondly,a wide-area robust sliding mode control algorithm based on estimation state is proposed.In which,a new sliding mode function is constructed and a new approach law is designed.Furthermore,the stability of the proposed algorithm is proved and the dynamic performance of the system is analyzed.Finally,the effectiveness of the algorithm is verified by a two-area four-machine power system and a five-area 16-machine 68-bus power system.