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RISS 인기검색어
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- 저자 : Xiucheng Liu (검색결과 2 건)
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Nonlinear Adaptive Control for Dynamic and Dead-zone Uncertainties in Robotic Systems
Xia Liu,Wei Jiang,Xiucheng Dong 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
Accurate position tracking performance of robotic systems with both dynamic and dead-zone uncertaintiesis difficult to achieve by traditional adaptive control. In this paper, for nonlinear robotic systems in the presenceof uncertain dynamics and dead-zone, an adaptive control scheme is employed to guarantee accurate and stable positiontracking. The dynamics of the robot and dead-zone parameters are concurrently estimated in the adaptationlaws and the estimated values are subsequently applied in the control law. In order to demonstrate the practicabilityof this paper, an experimental setup composed of Phantom Omni robots are built. The experimental results showthat even when the dynamic and dead-zone uncertainties simultaneously appear, the robot can well track any desiredposition trajectory.
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Quantitative evaluation of through-thickness rectangular notch in metal plates based on lamb waves
Na Zhao,Bin Wu,Xiucheng Liu,Keqin Ding,Yanan Hu,Mahmoud Bayat 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.71 No.6
Lamb wave technology is a promising technology in the field of structural health monitoring and can be applied in the detection and monitoring of defects in plate structures. Based on the reconstruction algorithm for the probabilistic inspection of damage (RAPID), a Lamb-based detection and evaluation method of through-thickness rectangular notches in metal plates was proposed in this study. The influences of through-thickness rectangular notch length and the angle between sensing path and notch length direction on signals were further explored through simulations and experiments. Then a damage index calculation method which focuses on both phase and amplitude difference between detected signals and baseline signals was proposed. Based on the damage index difference between two vertically crossed sensing paths which pass through the notch in a sensor network, the notch direction identification method was proposed. In addition, the notch length was determined based on the damage index distribution along sensing paths. The experimental results showed that the image reconstructed with the proposed method could reflect the information for the evaluation of notches.
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