虚假数据注入攻击下受扰移动机器人系统弹性STMPC方法研究

doi:10.3778/j.issn.1002-8331.2404-0023

摘要/Abstract

摘要： 针对受扰移动机器人系统自触发模型预测控制（self-triggered model predictive control，STMPC）在虚假数据注入（false data injection，FDI）攻击下的安全控制问题，提出了一种基于输入重构的弹性STMPC方法。结合自触发机制非周期采样特性和FDI攻击模型，设计了一种基于关键数据的输入重构机制，以减弱FDI攻击对被控系统的影响。根据状态误差的最优控制问题，设计了重构参数的确定方法，以保证系统在应用重构控制输入后的控制性能。详细分析了所提出弹性STMPC算法的稳定性以及算法可行性。通过仿真和实验验证了所提出算法的有效性。

关键词: 虚假数据注入攻击, 输入重构, 模型预测控制, 弹性控制, 自触发机制

Abstract: A resilient STMPC method based on input reconstruction is proposed to solve the security control problem of self-triggered model predictive control (STMPC) for mobile robot system with disturbance under false data injection (FDI) attack. Firstly, combining the aperiodic sampling characteristics of the self-triggered mechanism and a FDI attack model, an input reconstruction mechanism based on key data is designed to reduce the influence of FDI attack on the controlled system. Secondly, according to the optimal control problem of the state error, the method of determining the reconstruction parameter is designed to ensure the control performance of the system after applying the reconstruction control input. Furthermore, the stability and feasibility of the proposed resilient STMPC algorithm are analyzed in detail. Finally, the effectiveness of the proposed algorithm is verified by simulation and experiment.

Key words: false data injection attack, input reconstruction, model predictive control； resilient control self-triggered mechanism

孙香香, 马凯, 范昭, 贺宁. 虚假数据注入攻击下受扰移动机器人系统弹性STMPC方法研究[J]. 计算机工程与应用, 2025, 61(9): 304-314.

SUN Xiangxiang, MA Kai, FAN Zhao, HE Ning. Research on Resilient STMPC Method for Mobile Robot System with Disturbance Under False Data Injection Attack[J]. Computer Engineering and Applications, 2025, 61(9): 304-314.

参考文献

[1] 王旭, 朱其新, 朱永红. 面向二维移动机器人的路径规划算法综述[J]. 计算机工程与应用, 2023, 59(20): 51-66.
WANG X, ZHU Q X, ZHU Y H. Review of path planning algorithms for mobile robots[J]. Computer Engineering and Applications, 2023, 59(20): 51-66.
[2] 顾海艳, 陈亮, 王多点. 基于模型预测控制的无人机时空协同航迹规划[J]. 计算机工程与应用, 2021, 57(23): 270-279.
GU H Y, CHEN L, WANG D D. Space-time cooperative path planning for multi-UAV using model predictive control[J]. Computer Engineering and Applications, 2021, 57(23): 270-279.
[3] ZHANG H, CHENG P, SHI L, et al. Optimal DoS attack scheduling in wireless networked control system[J]. IEEE Transactions on Control Systems Technology, 2015, 24(3): 843-852.
[4] 李富强, 郜丽赛, 郑宝周, 等. 欺骗攻击下网络化系统事件触发安全控制[J]. 计算机工程与应用, 2021, 57(5): 264-270.
LI F Q, GAO L S, ZHENG B Z, et al. Event-triggered secure control for networked systems under deception attacks[J]. Computer Engineering and Applications, 2021, 57(5): 264-270.
[5] 叶丹, 靳凯净, 张天予. 网络攻击下的信息物理系统安全性研究综述[J]. 控制与决策, 2023, 38(8): 2243-2252.
YE D, JIN K J, ZHANG T Y. A survey on security of cyber-physical systems under network attacks[J]. Control and Decisions, 2023, 38(8): 2243-2252.
[6] SHEN J H, WENG P D, SHEN Y, et al. Distributed fusion estimation for nonlinear cyber physical systems with attacked control signals[J]. IEEE Systems Journal, 2022, 17(1): 1216-1223.
[7] ANNASWAMY A M, MALEKPOUR A R, BAROS S. Emerging research topics in control for smart infrastructures[J]. Annual Reviews in Control, 2016, 42: 259-270.
[8] FRANZE G, FAMULARO D, LUCIA W, et al. Cyber-physical systems subject to false data injections: a model predictive control framework for resilience operations[J]. Automatica, 2023, 152: 110957.
[9] YANG H, DAI L, XIE H H, et al. Resilient MPC under severe attacks on both forward and feedback communication channels[J/OL]. IEEE Transactions on Automation Science and Engineering: 1-14(2023-10-19) [2024-05-16]. https://doi.org/10.1109/TASE.2023.3323806.
[10] FRANZE G, LUCIA W, TEDESCO F. Resilient model predictive control for constrained cyber-physical systems subject to severe attacks on the communication channels[J].?IEEE Transactions on Automatic Control, 2021, 67(4): 1822-1836.
[11] 陈峰, 孙子文. 工业信息物理系统数据注入攻击的事件触发弹性控制[J]. 控制理论与应用, 2020, 37(10): 2134-2146.
CHEN F, SUN Z W. Event-triggered elastic control of data injection attacks in industrial cyber physical systems[J]. Control Theory and Applications, 2020, 37(10): 2134-2146.
[12] HU Z J, SU R, LING K V, et al. Resilient event-triggered MPC for load frequency regulation with wind turbines under false data injection attacks[J/OL]. IEEE Transactions on Automation Science and Engineering: 1-11(2023-11-29) [2024-05-16]. https://doi.org/10.1109/TASE.2023.3337006.
[13] HE N, SHI D W, CHEN T W. Self-triggered model predictive control for networked control systems based on first-order hold[J]. International Journal of Robust and Nonlinear Control, 2018, 28(4): 1303-1318.
[14] CUI D, LI H P. Dual self-triggered model-predictive control for nonlinear cyber-physical systems[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 52(6): 3442-3452.
[15] LU L, MACIEJOWSKI J M. Robust self-triggered MPC for constrained linear systems with additive disturbance[C]// Proceedings of the 2019 IEEE 58th Conference on Decision and Control, Nice, Dec 11-13, 2019. Piscataway: IEEE, 2020: 445-450.
[16] HASHIMOTO K, ADACHI S, DIMAROGONAS D V. Self-triggered model predictive control for nonlinear input-affine dynamical systems via adaptive control samples selection[J]. IEEE Transactions on Automatic Control, 2016, 62(1): 177-189.
[17] XABIER L, PABLO G N, ISMAEL E A, et al. Analysing encryption mechanisms and functional safety in a ROS-based architecture[J]. Journal of Software: Evolution and Process, 2020, 32(2): 2555-2564.
[18] AMIR H K, SIYAMAK S, SINGLETON. A lightweight and secure end-to-end encryption protocol for the sensor networks in the Internet of Things based on cryptographic ratchets[J]. The Journal of Supercomputing, 2021, 77(4): 3516-3554.
[19] MAUTHAN A, SENDHIL R. Hybrid GSW and DM based fully homomorphic encryption scheme for handling false data injection attacks under privacy preserving data aggregation in fog computing[J]. Journal of Ambient Intelligence and Humanized Computing, 2020,11(5): 5217-5231.
[20] GAO L, CHEN B, YU L. Fusion-based FDI attack detection in cyber-physical systems[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2019, 67(8): 1487-1491.
[21] LI H P, SHI Y. Event-triggered robust model predictive control of continuous-time nonlinear systems[J]. Automatica, 2014, 50(5): 1507-1513.
[22] SHI Y, ZHANG K. Advanced model predictive control framework for autonomous intelligent mechatronic systems: a tutorial overview and perspectives[J]. Annual Reviews in Control, 2021, 52: 170-196.
[23] BEN-ASHER J Z, RIMON E D. Time optimal trajectories for a car-like mobile robot[J]. IEEE Transactions on Robotics, 2022, 38(1): 421-432.
[24] 刘成良, 林洪振, 李彦明, 等. 农业装备智能控制技术研究现状与发展趋势分析[J]. 农业机械学报, 2020, 51(1): 1-18.
LIU C L, LIN H Z, LI Y M. Analysis on status and development trend of intelligent control technology for agricultural equipment[J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(1): 1-18.
[25] 姜天, 赵静. 基于信息融合的物流仓储管控一体化系统[J]. 物联网技术, 2020, 10(2): 49-51.
JIANG T, ZHAO J. Integrated logistics warehouse control system based on information fusion[J]. Internet of Things Technologies, 2020, 10(2): 49-51.