Optimal Output Feedback Fuzzy Control of Single-Link Robot Arm Model Based on Intermediate Variable Fault Estimate.

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Bibliographic Details
Title:	Optimal Output Feedback Fuzzy Control of Single-Link Robot Arm Model Based on Intermediate Variable Fault Estimate.
Authors:	Liu, Sihan¹ 1350907346@qq.com, Yan, Hailong² 1074501593@qq.com, Zhao, Lixia³ 396476831@qq.com
Source:	Engineering Letters. Aug2026, Vol. 34 Issue 8, p3245-3251. 7p.
Subjects:	Tracking control systems, Fault diagnosis, Lyapunov stability, Backstepping control method, Control theory (Engineering), Reinforcement learning, Fuzzy logic
Abstract:	This paper investigates the optimal output feedback tracking control problem for a single link robot arm subject to unknown time varying actuator faults and model uncertainties. To avoid the requirement for full state measurement, an intermediate variable fault estimator is developed to reconstruct the fault effect from the measured output and observer states. A fuzzy logic system is employed to approximate the lumped uncertain nonlinear dynamics. Based on the estimated states and fault information, an optimal backstepping output feedback control law is constructed. Furthermore, an actor critic learning scheme is introduced to improve the control policy with respect to prescribed infinite horizon performance indices. Lyapunov based analysis proves that all closed loop signals are uniformly ultimately bounded and that the tracking error converges to a small neighborhood of the origin. Simulation results on a single link robot arm verify the effectiveness of the proposed method in trajectory tracking, fault reconstruction, and robustness against model uncertainties. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	This paper investigates the optimal output feedback tracking control problem for a single link robot arm subject to unknown time varying actuator faults and model uncertainties. To avoid the requirement for full state measurement, an intermediate variable fault estimator is developed to reconstruct the fault effect from the measured output and observer states. A fuzzy logic system is employed to approximate the lumped uncertain nonlinear dynamics. Based on the estimated states and fault information, an optimal backstepping output feedback control law is constructed. Furthermore, an actor critic learning scheme is introduced to improve the control policy with respect to prescribed infinite horizon performance indices. Lyapunov based analysis proves that all closed loop signals are uniformly ultimately bounded and that the tracking error converges to a small neighborhood of the origin. Simulation results on a single link robot arm verify the effectiveness of the proposed method in trajectory tracking, fault reconstruction, and robustness against model uncertainties. [ABSTRACT FROM AUTHOR]
ISSN:	1816093X