Objective: In order to deal with the impact of cyber attack on the cyber-physical system of food picking robot. Methods: A method for states estimation and attacks detection of food picking robot system based on interval observer was proposed. Firstly, the digital model of the food picking robot located in the cyber-physical system was established, using Lagrange method to establish the dynamic equation of the manipulator and convert it into the state-space model, the network attacks model was constructed according to the feedback control strategy. Considering the nonlinear characteristics and noiseand applying the generalized system theory was applied to transform sensor attack into the system state, and the interval observer was designed as the attack detector, and the stability of errors system was proved. Results: The simulation results showed that observer output was close to the given real signal. The proposed method was correct and effective. The sensor attack can be reconstructed and the actuator attack can be detected from interval estimation results. Conclusion: The proposed method can realize states estimation and actuator attacks detection of food picking robot in cyber-physical system environment.

Publication Date


First Page


Last Page





[1] 毕宪东, 王振, 李朝龙. 基于Delta机器人的食品生产线动态目标抓取方法[J]. 食品与机械, 2022, 38(6): 117-122. BI X D, WANG Z, LI C L. Dynamic target grasping method of food production line based on Delta robot[J]. Food & Machinery, 2022, 38(6): 117-122.
[2] DAI J S, CALDWELL D G. Origami-based robotic paper-and-board packaging for food industry[J]. Trends in Food Science & Technology, 2010, 21(3): 153-157.
[3] BAGHERI M, NASERADINMOUSAVI P, KRSTIC M. Feedback linearization based predictor for time delay control of a high-DOF robot manipulator[J]. Automatica, 2019, 108: 108485.
[4] TALPUR M S H, SHAIKH M H. Automation of mobile pick and place robotic system for small food industry[J]. Computer Science, 2012, 11: 39-44.
[5] KHAN Z H, KHALID A, IQBAL J. Towards realizing robotic potential in future intelligent food manufacturing systems[J]. Innovative Food Science & Emerging Technologies, 2018, 48: 11-24.
[6] VANDERROOST M, RAGAERT P, VERWAEREN J, et al. The digitization of a food package's life cycle: Existing and emerging computer systems in the logistics and post-logistics phase[J]. Computers in Industry, 2017, 87: 15-30.
[7] IQBAL J, KHAN Z H, KHALID A. Prospects of robotics in food industry[J]. Food Science and Technology, 2017, 37: 159-165.
[8] CHUA P Y, ILSCHNER T, CALDWELL D G. Robotic manipulation of food products: A review[J]. Industrial Robot, 2003, 30(4): 345-354.
[9] HONG J, WANG D, GUAN Y. Synergistic integrated design of an electrochemical mechanical polishing end-effector for robotic polishing applications[J]. Robotics and Computer-Integrated Manufacturing, 2019, 55: 65-75.
[10] ZHAO M, ANZAI T, SHI F, et al. Versatile multilinked aerial robot with tilted propellers: Design, modeling, control, and state estimation for autonomous flight and manipulation[J]. Journal of Field Robotics, 2021, 38(7): 933-966.
[11] 杨超群, 张恒, 何立栋, 等. 基于随机有限集的信息物理系统状态估计[J]. 控制工程, 2022, 29(8): 1 424-1 428. YANG C Q, ZHANG H, HE L D, et al. State estimation of cyber physical system based on random finite set[J]. Control Engineering of China, 2022, 29(8): 1 424-1 428.
[12] NA J, JING B, HUANG Y, et al. Unknown system dynamics estimator for motion control of nonlinear robotic systems[J]. IEEE Transactions on Industrial Electronics, 2019, 67(5): 3 850-3 859.
[13] LEE J G, KIM J, SHIM H. Fully distributed resilient state estimation based on distributed median solver[J]. IEEE Transactions on Automatic Control, 2020, 65(9): 3 935-3 942.
[14] PESSIM P S P, PEIXOTO M L C, PALHARES R M, et al. Static output-feedback control for Cyber- physical LPV systems under DoS attacks[J]. Information Sciences: An International Journal, 2021, 563: 241-255.
[15] JAIN H, KUMAR M, JOSHI A M. Intelligent energy cyber physical systems (iECPS) for reliable smart grid against energy theft and false data in jection[J]. Electrical Engineering, 2022, 104: 331-346.
[16] BHARATH K P, KUMAR M R. New replay attack detection using iterative adaptive inverse filtering and high frequency band[J]. Expert Systems with Application, 2022, 195: 116597.
[17] ZHAO Z, HUANG Y, ZHEN Z, et al. Data-driven false data-injection attack design and detection in cyber-physical systems[J]. IEEE Transactions on Cybernetics, 2020, 51(12): 6 179-6 187.
[18] LUCIA W, GHEITASI K, GHADERI M. Set point attack detection in cyber-physical systems[J]. IEEE Transactions on Automatic Control, 2020, 66(5): 2 332-2 338.
[19] SAYAD HAGHIGHI M, FARIVAR F, JOLFAEI A, et al. Intelligent robust control for cyber-physical systems of rotary gantry type under denial of service attack[J]. The Journal of Supercomputing, 2020, 76(4): 3 063-3 085.
[20] 刘一帆, 左稳, 张之津, 等. 传感器网络DoS攻击下随机系统的故障检测设计[J]. 哈尔滨工程大学学报, 2022, 43(3): 377-384. LIU Y F, ZUO W, ZHANG Z J, et al. Fault detection design for uncertain systems over sensor network under DoS attacks[J]. Journal of Harbin Engineering University, 2022, 43(3): 377-384.
[21] GUO S, ZHU F, ZHU S, et al. State and sensor fault interval estimations for discrete- time systems[C]// 36th Chinese Control Conference (CCC). Dalian: IEEE, 2017: 7 280-7 284.
[22] GUO S, JIANG B, ZHU F, et al. Luenberger-like interval observer design for discrete-time descriptor linear system[J]. Systems & Control Letters, 2019, 126: 21-27.
[23] 张丹丹. 柔性关节机器人动力学建模及控制[D]. 南京: 南京理工大学, 2017: 12-22. ZHANG D D. Dynamic modeling and control of flexible joint robot[D]. Nanjing: Nanjing University of Science and Technology, 2017: 12-22.
[24] BAGULA A, AJAYI O, MALULEKE H. Cyber physical systems dependability using cps-iot monitoring[J]. Sensors, 2021, 21(8): 2 761.
[25] CACCAVALE F, CILIBRIZZI P, PIEER F, et al. Actuators fault diagnosis for robot manipulators with uncertain model[J]. Control Engineering Practice, 2009, 17(1): 146-157.
[26] TEIXEIRA A, SHAMES I, SANDBERG H, et al. A secure control framework for resource-limited adversaries[J]. Automatica, 2015, 51: 135-148.
[27] 孙子文, 张炎棋. 工业信息物理系统的攻击建模研究[J]. 控制与决策, 2019, 34(11): 2 323-2 329. SUN Z W, ZHANG Y Q. Research on attack modeling of industrial cyber physical systems[J]. Control and Decision, 2019, 34(11): 2 323-2 329.
[28] DE SOUZA A R, EFIMOV D, RAISSI T, et al. Robust output feedback model predictive control for constrained linear systems via interval observers[J]. Automatica, 2022, 135: 109951.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.