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RISS 인기검색어
- 검색키워드
- 저자 : Mien-Ka Duong (검색결과 2 건)
- 무료
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- 유료
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Minimizing Human-exoskeleton Interaction Force by Using Global Fast Sliding Mode Control
Duong Mien Ka,Cheng Hong,Tran Huu Toan,Jing Qiu 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.4
A critical issue in the model-based control of performance-augmenting exoskeleton systems is the unknownnonlinear dynamic properties of the systems or the uncertainties. An improper estimation of the systemdynamics can cause instabilities in the system and generate considerable human-exoskeleton interaction forcesduring human motions. Thus, the controller of such exoskeleton systems needs to add robustness to stabilize itagainst the uncertainties. In this paper, we propose a global fast sliding mode control algorithm integrated in ahybrid controller for each exoskeleton leg to minimize human-exoskeleton interaction forces. By doing so, theproposed algorithm does not require an exact estimation of the dynamic properties of the exoskeleton system, butstill minimizes the physical human-exoskeleton interaction (pHEI) forces. Finally, the performance of the proposedalgorithm is verified by experiments on our lower exoskeleton system, which is used for human power augmentationand called “PRMI” exoskeleton. Our experimental results show that the proposed control algorithm provides agood control quality for the PRMI exoskeleton. The PRMI exoskeleton can support a wearer carrying heavy loadwhile tracking the rapid movements of the wearer without obstructing them.
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Adaptive Wavelet CMAC Tracking Control for Induction Servomotor Drive System
Thanh-Quyen Ngo,Mien-Ka Duong,D. C. Pham,Duc-Nam Nguyen 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.1
This research proposes an enhanced control system for induction servomotor to obtain the high-precision position tracking based on wavelet cerebellar model articulation controller. The proposed controller combines the wavelet cerebellar articulation model (WCMAC) with compensator controller to have high performance for the system. The superior properties of the WCMAC are its fast learning of the CMAC and wavelet decomposition capability. Therefore, it is used to mimic a model-based controller with exactly unknown parameters. The compensator controller with an estimated boundary error attenuates the effects of disturbances due to time-varying parameters and load acting on the shaft of motor. The online learning rules of WCMAC derived from gradient-descent method and Lyapunov function is used to estimate bound error to ensure the stability of the system. The experimental results for induction servomotor are provided to conclude the effectiveness of the proposed control system even the dynamic model of the induction servomotor is completely unknown.
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