Research On Resilient Self-Triggered Model Predictive Control For Nonlinear Systems Under False Data Injection Attacks

Model predictive control(MPC)has been widely applied in electromechanical systems such as mobile robots and robotic arms due to its advantages of handling multivariate system input/output coupling and resolving physical constraints on system variables.With the fourth industrial revolution promoting the cyber-physical systems(CPS)technology in various industries,the physical components of traditional electromechanical systems,such as a controlled object,controller and sensor,are gradually connected to the cyber layer,and the performance of the system is further improved by using the network resources.However,due to the characteristics of openness and convergence of CPS,the controller and actuator are inevitably threatened by cyberattacks when interacting with each other through wireless networks.In addition,since traditional MPC needs to solve the optimal control problem(OCP)and transmit control signals periodically,this also increases the computational and communication burden of CPS.Therefore,it is of great theoretical and practical significance to develop resilient predictive control with a balance of defense against cyber-attacks and reduced resource consumption.In this paper,the nonlinear electromechanical system is studied to design the resilient self-triggered MPC(ST-MPC)strategy to defend against false data injection(FDI)attacks,which can ensure the cyber security of the controlled system and reduce the system resource consumption.The main research contents are as follows.First,a resilient ST-MPC strategy based on key information protection is proposed for nonlinear continuous-time systems.Based on the traditional ST-MPC discrete sampling characteristics and the FDI attack model,the quantitative influence of the system state change when different control data of the control sequence is attacked is obtained.A security control strategy based on key information protection is proposed,and the key control data of MPC control sequences that need to be additionally protected are determined.The resilient ST-MPC algorithm based on key control information protection is constructed,and the feasibility and closed-loop stability of the algorithm under FDI attack are critically demonstrated.In addition,the effectiveness of the algorithm is verified by combining the cart-damper-spring system and the mobile robot system,and the results show that the algorithm can effectively reduce the system resource consumption while defending against the FDI attack.Secondly,a resilient ST-MPC strategy based on input reconstruction is further proposed for nonlinear continuous-time systems.Based on the self-triggered aperiodic sampling characteristics and the FDI attack model,an input reconstruction mechanism based on key data is proposed,and the selection conditions of key data and the corresponding selection algorithm is designed by combining the input reconstruction mechanism and the stability theory,which can maximize the triggering interval while ensuring the stability of the system.The resilient ST-MPC algorithm based on the input reconstruction mechanism and key data selection algorithm is designed,and the feasible and closed-loop stability conditions of the proposed algorithm under FDI attack are derived.The simulation and comparison verify that the resilient ST-MPC algorithm based on input reconstruction can maintain better control performance and resource utilization under the premise of defending against FDI attack.Finally,the resilient ST-MPC strategy based on input reconstruction is further extended to nonlinear discrete-time systems.The input reconstruction mechanism for discrete system is constructed by combining the discrete ST-MPC characteristics and the FDI attack model,and the key data selection condition is obtained by introducing the Gronwall-Bellman-Bu-Iang-type inequality and the Input-to-State Stability(ISS)theory.Based on the input reconstruction mechanism and the key data selection condition,the resilient ST-MPC algorithm based on input reconstruction is designed for nonlinear discrete-time systems,and the iterative feasibility of the algorithm and the ISS performance of the controlled system under FDI attack are theoretically demonstrated.In addition,the torsion pendulum system and the intelligent vehicle system are combined for simulation verification.The results show that the proposed algorithm can not only defend against FDI attacks,but also effectively reduce the consumption of computation,communication and protection resources.