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Cited by 3Adaptive Control of Nonlinear SystemsStability and Control of Uncertain SystemsControl and Dynamics of Mobile Robots

Adaptive fuzzy fault‐tolerant control via integral terminal sliding mode of robotic systems with prescribed performance

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Zhang, Jie, Jiang, Wanyue, Sam Ge, Shuzhi·2025·Asian Journal of Control
DOI 10.1002/asjc.3590
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Abstract

This paper addresses the robust fault‐tolerant tracking control problem of robotic systems with actuator faults and model uncertainties under prescribed performance constraint. Firstly, an adaptive technique and fuzzy logic system are used to approximate the system model uncertainties and possible actuator faults. Secondly, a new fast integral terminal sliding mode backstepping control method is proposed, which makes the high robustness for the robotic systems when the actuator faults occur under the premise of ensuring the prescribed performance. Furthermore, a nonlinear disturbance observer is developed to estimate the lumped disturbance composed of external disturbance and approximation error, which enhances anti‐disturbance performance, reduces sliding mode chattering, and ensures high robustness of the entire robotic systems. Ultimately, the global asymptotic stability of the robotic systems is achieved based on the Lyapunov criterion. The simulation results confirm the effectiveness of the proposed control scheme.

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  • Manufacturing benefits from hybrid systems reducing downtime through parallel kinematics and adaptive control.

    “Manufacturing benefits from hybrid systems reducing downtime through parallel kinematics and adaptive control [38,41]”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [41]

    The Introduction (page not provided) places robotic control in a manufacturing context and says adaptive fault-tolerant control helps robots operate reliably when faults occur. The paper does not address hybrid systems, parallel kinematics, or reduced downtime, so it supports only the adaptive-control portion of the claim. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Integration of mechanical and electronic components increases costs.

    “However, integration increases costs [41]”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [41]

    The Introduction discusses robotic control challenges and controller design, but does not address the cost of integrating mechanical and electronic components. Searches for integration and cost-related terms found no passage supporting or contradicting the claim. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Hybrid AI methods integrating fuzzy logic, neural networks, and reinforcement learning with a three-layer fusion model improve efficiency in multi-agent human-robot collaboration with moderate overhead.

    “Hybrid Artificial Intelligence (AI) methods integrate fuzzy logic, neural networks, and RL with a three-layer fusion model, improving efficiency in multi-agent HRC [8,41], with moderate overhead [42].”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [41]

    The Introduction discusses fuzzy logic and neural networks for handling uncertainty in robotic control, while the Simulation Results examine a two-link robot. Neither passage addresses reinforcement learning, a three-layer fusion model, multi-agent human–robot collaboration, efficiency gains, or overhead. Searches for those terms found no supporting passage in our copy. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Hybrid mechanical-electronic systems offer a synergistic advantage over purely mechanical systems, which lack adaptability, and electronic-only approaches prone to hardware limits.

    “Compared to purely mechanical systems, which lack adaptability, or electronic-only approaches prone to hardware limits, hybrid systems offer a synergistic advantage, as seen in manufacturing with dual-drive redundancy reducing motor power [41] and surgery with efficient laparoscopic outcomes [31].”

    From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [41]

    The Introduction discusses adaptive fault-tolerant control for robotic systems, and the Simulation Results concern a two-link robot. Neither section addresses hybrid mechanical-electronic systems, their comparison with purely mechanical or electronic-only approaches, or laparoscopic outcomes (searched: laparoscopic surgery, hybrid mechanical-electronic systems, and hardware limits). (LLM, conf=0.76)

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  37. where he is also a professor with the Department of Electrical and Computer Engineering. He is also the honorary director of the Institute for Future (IFF), Qingdao University, Qingdao, China. His current research interests include robotics, intelligent systems, artificial intelligence, and smart materials. Prof. Ge is also a fellow of International Federation of Auto- matic Control (IFAC), Institution of Engineering and Technology (IET). He is also the editor-in-chief of the International Journal of Social Robotics (Springer). He has been serving as an associate editor for a number of flagship journals, including the IEEE Transactions on Automatic Control, the IEEE Transactions on Control Systems Technology, the IEEE Transactions on Neural Networks and Learning Systems, the IEEE Transactions on Systems, Man, and Cybernetics: Systems, Automatica, and the CAAI Transactions on Intelligence Technology. How to cite this article: J. Zhang, W. Jiang, and S. Ge, Adaptive fuzzy fault-tolerant control via inte- gral terminal sliding mode of robotic systems with pre- scribed performance. Asian J. Control 27 (2025), DOI 10.1002/asjc.3590. 2465-2475,

Cited by

Sorted by citations

Authors
Zhang, J., Jiang, W., & Sam Ge, S.
Affiliations
  • Qingdao University (CN)
  • Institute for Future, School of Automation Qingdao University Shandong China
ORCID
Venue
Asian Journal of Control
Publisher
Wiley
Published
2025-01-23
Volume
27
Issue
5
Pages
2465-2475
ISSN
  • 1561-8625 (ISSN-L)
  • 1934-6093
DOI
10.1002/asjc.3590
OpenAlex
W4406762827
Cited by
3
References
0
Citations by year
2025: 3
FWCI
1.11
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
Asian Journal of Control (publishedVersion)
Funders
National Natural Science Foundation of China (62303256)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Control and Dynamics of Mobile Robots
Keywords
fault-tolerant control, robot manipulators, actuator faults, prescribed performance, backstepping control, adaptive fuzzy control, fuzzy systems, nonlinear disturbance observer, model uncertainty, tracking control, chattering reduction, global asymptotic stability

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