Design and experimental verification: Health indicator-based decentralized optimal fault-tolerant control for modular robot manipulators via adjustable event-triggered mechanism
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Gain scheduling has broad applicability with at least 90% accuracy.
“highlighting neural-adaptive control's precision (up to 94% accuracy [11]) and gain scheduling's broad applicability (≥90% accuracy [33]).”
From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [33]
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Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability
Urrea, C. (2025) · Actuators · doi:10.3390/act14040177 · Cited by 19 · see citing works
“Table 2 compares AFTC methodologies, highlighting neural-adaptive control’s precision (up to 94% accuracy [11]) and gain schedul-ing’s broad applicability ( ≥ 90% accuracy [33]).”
- Authors
- Pan, Q., Ma, B., An, T., Dong, B., Zhu, M., & Li, Y.
- Affiliations
- Changchun University of Technology (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Li, Yuanchun
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 243
- Pages
- 122944
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W4389776463
- Cited by
- 9
- References
- 0
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 2
- FWCI
- 1.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Expert Systems with Applications (publishedVersion)
- Funders
- National Natural Science Foundation of China (62173047)
- Jilin Provincial Scientific and Technological Development Program (20230101178JC, 20230508159RC)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Adaptive Dynamic Programming Control
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Keywords
- modular robot manipulators, fault-tolerant control, health indicators, event-triggered control, decentralized control, approximate dynamic programming, Hamilton-Jacobi-Bellman equation, joint torque feedback, robust compensator, actuator fault diagnosis, uniform ultimate boundedness
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