Browsing by Author "Weng, Mao-Chiao"

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A Dual-Model Fault Detection Approach with Application to Actuators of Robot Manipulators
(2011)
Hsiao, Tesheng
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Weng, Mao-Chiao
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電機工程學系
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Department of Electrical and Computer Engineering
Multiple-model (MM)-based methods have been successfully applied to many fault detection schemes; however systematic design of the associated model set remains an open question. The difficulty comes from the fact that using a large model set reduces the risk of undetected faults, but also increases the computation load drastically. In this paper we propose a dual-model fault detection (DMFD) algorithm aiming at solving the model set design problem, and apply it to detect actuator faults of robot manipulators. The DMFD algorithm is able to detect various types of unexpected actuator faults, including abrupt faults, incipient faults, and simultaneous faults, in a computationally efficient way. To evaluate the performance of the DMFD algorithm, upper bounds of the false alarm and missed detection probabilities are explicitly presented in terms of the tunable variables. Furthermore, experiments are conducted to demonstrate its ability in immediate detection of faults.
A hierarchical multiple-model approach for detection and isolation of robotic actuator faults
(2012-02-01)
Hsiao, Tesheng
;
Weng, Mao-Chiao
;
電機工程學系
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Department of Electrical and Computer Engineering
Modern robotic systems perform elaborate tasks in complicated environments and have close interactions with humans. Therefore fault detection and isolation (FDI) schemes must be carefully designed and implemented on robotic systems in order to guarantee safe and reliable operations. In this paper, we propose a hierarchical multiple-model FDI (HMM-FDI) scheme to detect and isolate actuator faults of robot manipulators. The proposed algorithm performs FDI in stages and refines the associated model set at each stage. Consequently only a small number of models are required to detect and isolate various types of unexpected actuator faults, including abrupt faults, incipient faults, and simultaneous faults. In addition, the computational load is alleviated due to the reduced-sized model set. The relation between the fault detection stage of the HMM-FDI scheme and the likelihood ratio test is explicitly revealed and theoretical upper bounds of the false alarm and missed detection probabilities are evaluated. Then we conduct experiments to demonstrate the ability of the HMM-FDI scheme in successful and immediate detection and isolation of actuator faults. (C) 2011 Elsevier B.V. All rights reserved.
Robust Joint Position Feedback Control of Robot Manipulators
(2013-05-01)
Hsiao, Tesheng
;
Weng, Mao-Chiao
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電機資訊學士班
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電控工程研究所
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Undergraduate Honors Program of Electrical Engineering and Computer Science
Most manipulator motion controllers require joint velocity feedback. Whenever joint velocities are not measurable, they are estimated from the joint positions. However, velocity estimates tend to be inaccurate under low-speed motion or low sensor resolution conditions. Moreover, velocity estimators may either be susceptible to model uncertainties or introduce additional dynamics (e. g., phase lag) to the control loop. Consequently, direct substitution of velocity estimates into the controller results in the deterioration of the control performance and robustness margin. Therefore, this paper proposes a robust position-feedback motion controller which gets rid of the problems of uncompensated dynamics and model uncertainties introduced by velocity estimators. Furthermore, a globally asymptotically stable system, which is robust with respective to model parameter variations, is guaranteed. Theoretical analysis and experimental verifications are carried out. The results demonstrate that the proposed controller is robust and outperforms the conventional computed torque plus proportional integral differential (PID) controller.