Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults

Xu, Haiying; Yang, Qiyao; Cai, Jianping; Zhu, Chen; Mei, Congli

doi:10.3390/electronics14101917

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Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults

by

Haiying Xu

^1,2,

Qiyao Yang

^1,2,*

,

Jianping Cai

^1,2

,

Chen Zhu

¹ and

Congli Mei

¹

College of Electrical Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China

²

Zhejiang-Belarus Joint Laboratory of Intelligent Equipment and System for Water Conservancy and Hydropower Safety Monitoring, Hangzhou 310018, China

^*

Author to whom correspondence should be addressed.

Electronics 2025, 14(10), 1917; https://doi.org/10.3390/electronics14101917

Submission received: 25 March 2025 / Revised: 1 May 2025 / Accepted: 7 May 2025 / Published: 8 May 2025

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Abstract

A prescribed performance neuro-adaptive control scheme is proposed for a single-link flexible-joint robotic manipulator with unknown deadzone and actuator faults. A new smooth deadzone inverse model is constructed to offset the adverse effect caused by the input deadzone in the actuator of flexible-joint manipulators. The control law is developed by coordinating prescribed performance control with a backstepping technique to ensure transient/steady-state performance, while adaptive neural networks are employed for uncertainty approximation. The tracking error is always restricted within the prescribed bound during the control process, and it ultimately converges to the small neighborhood of origin. All signals in the closed-loop flexible-joint robotic manipulator system are proved to be uniformly bounded. Simulation results are provided to demonstrate the efficiency of the prescribed performance adaptive neural network backstepping control scheme.

Keywords: adaptive control; flexible-joint robotic manipulator; prescribed performance; deadzone; backstepping control; neural network

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MDPI and ACS Style

Xu, H.; Yang, Q.; Cai, J.; Zhu, C.; Mei, C. Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults. Electronics 2025, 14, 1917. https://doi.org/10.3390/electronics14101917

AMA Style

Xu H, Yang Q, Cai J, Zhu C, Mei C. Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults. Electronics. 2025; 14(10):1917. https://doi.org/10.3390/electronics14101917

Chicago/Turabian Style

Xu, Haiying, Qiyao Yang, Jianping Cai, Chen Zhu, and Congli Mei. 2025. "Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults" Electronics 14, no. 10: 1917. https://doi.org/10.3390/electronics14101917

APA Style

Xu, H., Yang, Q., Cai, J., Zhu, C., & Mei, C. (2025). Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults. Electronics, 14(10), 1917. https://doi.org/10.3390/electronics14101917

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Adaptive Prescribed Performance Control for Flexible-Joint Robotic Manipulators with Unknown Deadzone and Actuator Faults

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