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Hybrid fuzzy-MPC approach for secure consensus in time-delayed multi-robot networks under sensor and actuator attacks | ||
| Iranian Journal of Fuzzy Systems | ||
| دوره 23، شماره 5، آذر و دی 2026، صفحه 37-66 اصل مقاله (3.29 M) | ||
| نوع مقاله: Original Manuscript | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2026.53689.9505 | ||
| نویسندگان | ||
| Ping Yu1؛ Waqar Ul Hassan2؛ Abeeha Mishal2؛ Aseel Smerat3؛ Azmat Ullah Khan Niazi* 4؛ Naveed Iqbal5 | ||
| 1Hefei Technology College, Hefei, 230012, Anhui, PR China | ||
| 2Department of Mathematics, Faculty of Sciences, University of Mianwali, 42200, Mianwali, Punjab, Pakistan | ||
| 3Faculty of Educational Sciences, Al-Ahliyya Amman University, Amman 19328, Jordan | ||
| 4Department of Mathematics and Statistics, The University of Lahore, Sargodha 40100, Pakistan | ||
| 5Department of Mathematics, College of Science University of Ha’il, Ha’il 2440, Saudi Arabia. | ||
| چکیده | ||
| This paper addresses the consensus problem in multi-robot systems subject to time delays, unknown nonlinearities, and cyber-physical attacks. To effectively handle uncertainties and mitigate the adverse effects of malicious disruptions, a Type-3 fuzzy logic system is introduced to construct a robust hybrid control framework. The considered network is exposed to sensor attacks, actuator attacks, and Byzantine disruptions, where particular emphasis is placed on mitigating sensor and actuator attacks. The proposed controller is designed to achieve two main objectives: minimizing the consensus error among robots and maintaining balanced update behavior during communication processes. Further more, a constrained control strategy based on Model Predictive Control (MPC) is incorporated to optimize resource utilization and enhance system security. By embedding security constraints into the MPC formulation, the proposed approach effectively reduces the influence of sensor attacks on the networked robots. To validate the effectiveness of the developed framework, the Duffing-Holmes chaotic system is employed as a benchmark model, demonstrating improved performance under communication delays and cyber-physical disturbances. In addition, Lyapunov-Krasovskii functional analysis combined with Linear Matrix Inequalities (LMIs) is utilized to establish the convergence and stability conditions of the multi-robot network. Finally, extensive simulation results are provided to verify the theoretical findings and demonstrate the robustness and effectiveness of the proposed strategy under attack scenarios and time-delay conditions. | ||
| کلیدواژهها | ||
| Multi-robot systems؛ consensus control؛ cyber-physical attacks؛ Type-3 fuzzy logic؛ model predictive control (MPC)؛ time-delay systems؛ byzantine fault tolerance؛ duffing-Holmes chaotic system | ||
| مراجع | ||
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[1] B. Cai, S. Zhang, H. Zhu, X. Ju, Y. Zhao, Manifold-constraint anti-disturbance subspace predictive control for unmodeled free-floating space robot maneuvering, Aerospace Science and Technology, 177(Part B) (2026), 112256. https://doi.org/10.1016/j.ast.2026.112256
[2] P. Chen, Y. Song, Y. Xia, Adaptively diagnosing system faults in microservice architecture: An autonomous predictive model construction framework, Future Generation Computer Systems, 177 (2026), 108256. https: //doi.org/10.1016/j.future.2025.108256
[3] Q. Chen, R. Wu, D. Schott, J. Jovanova, Programmable structure with shape memory materials for soft robotics, Smart Materials and Structures, 35(1) (2026), 15049. https://doi.org/10.1088/1361-665X/ae2a8
[4] J. Chen, C. Yu, Y. Wang, Z. Zhou, Z. Liu, Hybrid modeling for vehicle lateral dynamics via AGRU with a dual attention mechanism under limited data, Control Engineering Practice, 151 (2024), 106015. https://doi.org/ 10.1016/j.conengprac.2024.106015
[5] F. Ding, Z. Liu, Y. Wang, et. al., Intelligent event triggered lane keeping security control for autonomous vehicle under DoS attacks, IEEE Transactions on Fuzzy Systems, 33(10) (2025), 3595-3608. https://doi.org/10.1109/ TFUZZ.2025.3597276
[6] X. Du, J. Zhu, J. Zhou, et. al., DP-TRAE: A dual-phase merging transferable reversible adversarial example for image privacy protection, IEEE Transactions on Dependable and Secure Computing, 22(6) (2025), 7849-7861. https://doi.org/10.1109/TDSC.2025.3601175
[7] S. Fan, J. Chang, Z. Wang, et. al., Research on adaptive cooperative positioning algorithm for underwater robots based on dolphin group cooperative mechanism, Biomimetics, 11(1) (2026), 82. https://doi.org/10.3390/ biomimetics11010082
[8] B. Feng, Z. Wang, L. Yuan, Q. Zhou, Y. Chen, Y. Bi, Towards safe motion planning for industrial human-robot interaction: A co-evolution approach based on human digital twin and mixed reality, Robotics and Computer Integrated Manufacturing, 95 (2025), 103012. https://doi.org/10.1016/j.rcim.2025.103012
[9] Y. Fu, B. Wang, H. Zhao, M. Zhou, N. Li, Z. Gao, Adaptive safety attitude control of a hybrid VTOL UAV under transition flight subject to multiple faults and uncertainties, Aerospace Science and Technology, 163 (2025), 110284. https://doi.org/10.1016/j.ast.2025.110284
[10] Y. Guan, L. Yang, Z. Li, et. al., A novel variable-morphology soft robot inspired by inchworms and pangolins using a combination of magnetoelastic and thermoelastic materials, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 747 (2026), 140889. https://doi.org/10.1016/j.colsurfa.2026.140889
[11] W. Guo, J. Liu, W. Qin, X. Lan, H. Bai, X. Li, Robust adaptive dynamic programming for morphing air breathing hypersonic vehicles under unmatched uncertainty, Science China Information Sciences, 69(2) (2026), 122205. https://doi.org/10.1007/s11432-024-4386-4
[12] C. Guo, G. Zhong, Z. Xiao, D. Wang, Detecting faulty substructures in networks, IEEE Transactions on Computers, 75(5) (2026), 1937-1948. https://doi.org/10.1109/TC.2026.3661204
[13] F. Hongguang, K. Shi, A. Zhou, F. Meng, L. Jiang, Exploring fixed-time synchronization of fractional-order fuzzy cellular neural networks with information interactions and time-varying delays via adaptive multi-module control, Fractal and Fractional, 10(4) (2026), 253. https://doi.org/10.3390/fractalfract10040253
[14] M. Hou, J. Zhao, J. Tian, H. Du, Minimum operator-based data-driven sliding mode control for a magnetorheological fluid dual clutch, IEEE Transactions on Cybernetics, 55(10) (2025), 4991-5001. https://doi.org/10.1109/TCYB. 2025.3596063
[15] Y. Hou, S. Zhong, Z. Zheng, Magnetic shaftless propeller millirobot with multimodal motion for small-scale fluidic manipulation, Cyborg and Bionic Systems, 6 (2025), 0235. https://doi.org/10.34133/cbsystems.0235
[16] M. Huo, Z. Fan, J. Qi, N. Qi, D. Zhu, Fast analysis of multi-asteroid exploration mission using multiple electric sails, Journal of Guidance, Control, and Dynamics, 46(5) (2023), 1015-1022. https://doi.org/10.2514/1.G006972
[17] Y. Jiang, P. Chen, Q. Guo, et. al., A novel posture optimization method based on the comprehensive stiffness performance index in robotic milling, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 48(6) (2026), 445. https://doi.org/10.1007/s40430-026-06446-y
[18] J. Jin, L. Zhao, L. Chen, W. Chen, A robust zeroing neural network and its applications to dynamic complex matrix equation solving and robotic manipulator trajectory tracking, Frontiers in Neurorobotics, 16 (2022), 1065256. https://doi.org/10.3389/fnbot.2022.1065256
[19] Y. Kang, L. Yao, H. Wang, Fault isolation and fault-tolerant control for Takagi–Sugeno fuzzy time-varying delay stochastic distribution systems, IEEE Transactions on Fuzzy Systems, 30(4) (2022), 1185-1195. https://doi.org/ 10.1109/TFUZZ.2021.3053320
[20] R. Li, J. Jin, D. Zhang, C. Chen, A segmented activation function-based zeroing neural network model for dynamic Sylvester equation solving and robotic manipulator control, Concurrency and Computation: Practice and Experience, 37(21-22) (2025), e70243. https://doi.org/10.1002/cpe.70243
[21] G. Li, X. Liang, J. Zhang, T. Su, Z. Hou, A stiffness-enhanced extensible continuum surgical robot: Design, modeling, and evaluation, IEEE/ASME Transactions on Mechatronics, 31(1) (2025), 413-424. https://doi.org/ 10.1109/TMECH.2025.3592964
[22] D. Li, S. Ren, H. Wang, J. Liu, S. S. Ge, Randomized average consensus based on additive privacy sharing, Automatica, 186 (2026), 112847. https://doi.org/10.1016/j.automatica.2026.112847
[23] F. J. Li, H. Y. Zhang, Z. L. Lu, et. al., Unsupervised learning enabled label-free single-pixel imaging for resilient information transmission through unknown dynamic scattering media, Opto-Electronic Advances, 8(10) (2025), 250013. https://doi.org/10.29026/oea.2025.250013
[24] W. Liang, X. Sun, Y. Ji, J. Wu, X. Liu, Anonymous dynamic formation control of multiagent systems with obstacle avoidance, IEEE Transactions on Reliability, 75 (2026), 1079-1093. https://doi.org/10.1109/TR.2026.3665586
[25] Q. Liu, P. Chen, K. Lin, K. Zhao, J. Ding, Y. Li, Sample-efficient backtrack temporal difference deep reinforcement learning, Knowledge-Based Systems, 330(Part B) (2025), 114613. https://doi.org/10.1016/j.knosys.2025.114613
[26] R. Liu, Y. Fan, et. al., Design and workspace analysis of a cable-driven space capture robot for noncooperative targets, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 238(14) (2024), 1406-1418. https://doi.org/10.1177/09544100241272826
[27] Q. Liu, Z. Song, Y. Liang, Z. Xie, et. al., CoRLHF: Reinforcement learning from human feedback with cooperative policy-reward optimization for LLMs, Expert Systems with Applications, 301 (2026), 130113. https://doi.org/ 10.1016/j.eswa.2025.130113
[28] X. Liu, C. Wu, S. Zhen, H. Sun, C. Sun, Y. Chen, Robust control under servo constraint following via Nash equilibrium theory for bimanual humanoid manipulation, IEEE Transactions on Fuzzy Systems, 33(11) (2025), 4069-4082. https://doi.org/10.1109/TFUZZ.2025.3609828
[29] R. Liu, H. Yang, W. Li, et. al., Intelligent form-finding and optimization of six-bar tensegrity deployable antennas for enhanced prestress distribution and surface accuracy, Structural and Multidisciplinary Optimization, 69(5) (2026), 131. https://doi.org/10.1007/s00158-026-04339-1
[30] Z. Lu, X. Zhang, X. Cao, J. Hou, X. Yuan, SFEP-YOLO: A track obstacle detection model for autonomous electric locomotives in underground mine, IEEE Transactions on Vehicular Technology, 75(6) (2026), 9687-9700. https://doi.org/10.1109/TVT.2026.3651888
[31] Z. Luan, W. Zhao, C. Wang, Coordinated tracking control of the integrated wheel-end system based on generalized instantaneous steering center constraint, IEEE Transactions on Transportation Electrification, 11(3) (2025), 8271 8281. https://doi.org/10.1109/TTE.2025.3538892
[32] G. Nongyue, X. Changchuan, A. Chao, C. Zhiying, S. Chen, Unified aeroelastic and flight dynamics formulation based on state-space unsteady aerodynamics, AIAA Journal, 64(5) (2026), 1-18. https://doi.org/10.2514/1. J065498
[33] Y. Shi, Z. Li, Z. Yang, et. al., Neural-based adaptive grinding force tracking control for pneumatic end-actuator with uncertain dynamic model constraints, Information Sciences, 728 (2026), 122813. https://doi.org/10.1016/ j.ins.2025.122813
[34] Y. Sun, H. Sun, J. Ma, et. al., Multimodal agent AI: A survey of recent advances and future directions, Journal of Computer Science and Technology, 40(4) (2025), 1046-1063. https://doi.org/10.1007/s11390-025-4802-8
[35] Y. Tian, H. Tian, A multi-layer dynamic model of information propagation considering individual three-phase linear modulated behaviors, Physica A: Statistical Mechanics and its Applications, 689 (2026), 131427. https: //doi.org/10.1016/j.physa.2026.131427
[36] Q. Wang, J. Cao, H. Liu, Adaptive fuzzy control of nonlinear systems with predefined time and accuracy, IEEE Transactions on Fuzzy Systems, 30(12) (2022), 5152-5165. https://doi.org/10.1109/TFUZZ.2022.3169852
[37] G. Wang, Z. Feng, Y. Qu, H. Sun, Event-triggered adaptive predefined-time anti-unwinding attitude tracking control for spacecraft, PLoS One, 20(10) (2025), e0333700. https://doi.org/10.1371/journal.pone.0333700
[38] W. Wang, J. Jiang, W. Wang, et. al., Design and analysis of a self-orienting wireless power transfer system for the multifunctional capsule robot, IEEE Transactions on Power Electronics, 41(5) (2026), 8624-8635. https: //doi.org/10.1109/TPEL.2025.3635774
[39] Y. Wang, Z. Zhang, X. Yuan, X. Yin, Constraint control of electro-hydraulic position servo system based on command filter, Transactions of the Canadian Society for Mechanical Engineering, 50 (2026), 1-12. https://doi. org/10.1139/tcsme-2025-0142
[40] M. Wang, D. Zhou, M. Chen, Hybrid variable monitoring: An unsupervised process monitoring framework with binary and continuous variables, Automatica, 147 (2023), 110670. https://doi.org/10.1016/j.automatica. 2022.110670
[41] T. Wang, Z. Zhu, X. Zhou, T. Jing, W. Chen, A function-based behavioral modeling method for air combat simulation, Journal of Systems Engineering and Electronics, 35(4) (2024), 945-954. https://doi.org/10.23919/JSEE. 2024.000068
[42] W. Xiao, C. Xie, Y. Xiao, et. al., A new vacuum-powered soft bending actuator with programmable variable curvatures, Materials and Design, 250 (2025), 113641. https://doi.org/10.1016/j.matdes.2025.113641
[43] J. Xie, H. Liu, S. Nie, C. Xiang, L. Han, Jumping in legged robots: A review of advances in jumping abilities, methods, challenges, and future directions, Robotics and Autonomous Systems, 201 (2026), 105434. https:// doi.org/10.1016/j.robot.2026.105434
[44] J. Xiong, X. Wang, Adaptive sliding mode control for uncertain tilting quadrotors using randomized feedforward neural networks, International Journal of Robust and Nonlinear Control, 36(7) (2026), 4042-4055. https://doi. org/10.1002/rnc.70396
[45] F. Xu, S. Feng, Y. Wang, J. Chang, C. Zhou, Efficient deep reinforcement learning with expert demonstrations for human-machine shared steering control under emergency obstacle avoidance conditions, IEEE Transactions on Vehicular Technology, 75(5) (2026), 7356-7367. https://doi.org/10.1109/TVT.2025.3629701
[46] Z. Xu, K. Wang, C. Mu, T. Qiu, Safety-critical path planning for obstacle avoidance based on reinforcement learning and control barrier functions, IEEE Internet of Things Journal, 12(23) (2025), 51410-51421. https: //doi.org/10.1109/JIOT.2025.3614857
[47] Z. Yan, Z. Pan, G. Hu, J. Cheng, W. Qi, Annular finite-time H2/H∞ control for mean-field jump-diffusion systems, IEEE Transactions on Cybernetics, 55(11) (2025), 5358-5371. https://doi.org/10.1109/TCYB.2025.3597588
[48] Z. Yang, J. Shu, J. Jiang, et. al., Automated path-planning strategy for robotic inspection of underground utilities based on building information model, Computer-Aided Civil and Infrastructure Engineering, 40(29) (2025), 5554 5575. https://doi.org/10.1111/mice.70107
[49] X. Yang, X. Zhang, J. Cao, H. Liu, Observer-based adaptive fuzzy fractional backstepping consensus control of uncertain multiagent systems via event-triggered scheme, IEEE Transactions on Fuzzy Systems, 32(7) (2024), 3953-3967. https://doi.org/10.1109/TFUZZ.2024.3386312
[50] Z. Yang, W. Zhao, J. Kou, et. al., Observer-based fuzzy adaptive dynamic surface force control for pneumatic polishing system end-effector with uncertain contact environment model, IEEE Transactions on Automation Science and Engineering, 22 (2025), 17898-17913. https://doi.org/10.1109/TASE.2025.3585136
[51] C. Ye, Y. Yao, W. Lin, X. Yang, J. Qiu, CSGrasp: Category-level semantically-aware grasping method, IEEE Transactions on Industrial Electronics, 73(2) (2026), 2610-2619. https://doi.org/10.1109/TIE.2025.3605439
[52] W. Yuan, J. Chen, S. Chen, D. Feng, et. al., Transformer in reinforcement learning for decision-making: A survey, Frontiers of Information Technology and Electronic Engineering, 25(6) (2024), 763-790. https://doi.org/10. 1631/FITEE.2300548
[53] Z. Zhang, R. He, B. Han, S. Ren, J. Fan, H. Wang, Z. Ma, Magnetically switchable adhesive millirobots for universal manipulation in both air and water, Advanced Materials, 37(26) (2025), 2420045. https://doi.org/ 10.1002/adma.202420045
[54] Y. Zhang, Y. Shen, Y. C. Soh, et. al., Directionally regularized two-stage calibration for cross-shaped MGT sensor arrays with physics-inspired error modeling, IEEE Transactions on Instrumentation and Measurement, 75 (2026), 1-12. https://doi.org/10.1109/TIM.2026.3660392
[55] Y. Zhang, Y. Wang, C. Su, et. al., Multi-sensor fusion-based intelligent auxiliary system of power wheelchairs for individuals with limbs disabilities: Design and implementation, Measurement, 257(Part A) (2026), 118573. https://doi.org/10.1016/j.measurement.2025.118573
[56] S. Zhen, W. Ye, X. Liu, A leakage-type adaptive robust control method for collaborative robot joints with fuzzy uncertainty: Trajectory constraints and parameter optimization, Information Sciences, 754 (2026), 123674. https: //doi.org/10.1016/j.ins.2026.123674
[57] H. Zhong, H. Zhang, S. Zhen, et. al., Adaptive robust control for underactuated bipedal parallel wheel-legged robots: A Nash game-based constraint following approach, IEEE Transactions on Fuzzy Systems, 34(6) (2026), 1791-1803. https://doi.org/10.1109/TFUZZ.2026.3670620
[58] M. Zhong, J. Zhang, G. Zheng, H. Liu, Data–driven model–free adaptive dynamic programming resilient control for nonlinear networked control systems under DoS attacks, IEEE Transactions on Cybernetics, 55(12) (2025), 5700-5713. ://doi.org/10.1109/TCYB.2025.3594793
[59] L. Zhou, Z. Li, Y. Li, S. Bai, Parallel MPPI with gradient-velocity modulated SDF cost for high-performance real time dynamic obstacle avoidance by robot manipulators, IEEE Transactions on Robotics, 41 (2025), 5149-5168. https://doi.org/10.1109/TRO.2025.3600125
[60] X. Zhou, L. Li, X. Zhang, S. Jin, et. al., A seventy-year review of Dubins robot path planning: Basics, developments and opportunities, Industrial Robot: The International Journal of Robotics Research and Application, (2026), 1-23. https://doi.org/10.1108/IR-07-2025-0265
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آمار تعداد مشاهده مقاله: 5 تعداد دریافت فایل اصل مقاله: 5 |
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