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        Learning-based Adaptive Optimal Impedance Control to Enhance Physical Human-robot Interaction Performance

        Yida Guo,Yang Tian,Haoping Wang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.9

        This paper presents a framework of adaptive optimal impedance control to enhance physical humanrobot interaction (pHRI) performance. The overall structure of the proposed control scheme consists of an outer control loop and an inner control loop. In the outer control loop, a cost function that considers human motion and interaction force is minimized to optimize the overall human-robot interaction performance. An adaptive impedance controller is designed based on a Q-learning algorithm to realize impedance adaptation and guarantee the impedance parameters converge to the optimal value with completely unknown dynamics of the human limb. Then, a torque controller is developed in the inner control loop to enable the robot respond follow the obtained impedance model. In this controller, a novel barrier Lyapunov function (BLF) is employed to guarantee the error constraint and radial basis function neural networks (RBFNNs) are utilized to approximate the unknown robot dynamics. Stability and uniform boundedness of the closed-loop system are validated. Numerical simulation studies are performed to verify the effectiveness of the proposed controller.

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        Adaptive Event-triggered Cooperative Tracking Control Under Full-state Constraints Based on Nonlinear Time-varying Multi-agent Systems

        Lingfang Sun,Yida Zang,Xiuyu Zhang,Guoqiang Zhu,Cheng Zhong,Chenliang Wang 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.3

        An adaptive dynamic surface control (DSC) scheme using event triggering mechanism and barrier Lyapunov function (BLF) to constraint state variables and solve energy saving issues is proposed for multi-agent systems (MASs). Furthermore, invented a control algorithm that uses the event-triggered mechanism for not only decrease the number of information exchanges between agents significantly but also decreased utilization of electricityand communication expenses in the control process. DSC and full-state constraints are used to solve the “complexityexplosion” problem of the traditional back-stepping method. Simulation and semi-physical experimental platformswere constructed to verify the proposed algorithm is valid.

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        Experimental studies on torsional stiffness of cycloid gear based on machining parameters of tooth surfaces

        Zhifeng Liu,Tao Zhang,Yida Wang,Congbin Yang,Yongsheng Zhao 한국정밀공학회 2019 International Journal of Precision Engineering and Vol.20 No.6

        Estimating the torsional stiffness has always been the primary issue in analyzing the dynamic characteristics of cycloid gears. The traditional method of obtaining torsional rigidity involves calculating the ratio of the input torque and rotation angle, treating the deformation of cycloid gear as a black box. In order to thoroughly understand the rotation angle caused by the local contact deformation of each cycloid pin gear, a Majumdar–Bhushan contact model and the finite element method are combined to express the normal contact stiffness. By multiplying the normal contact stiffness of each pin gear and the arm of normal contact force, the torsional stiffness of the cycloidal pin wheel system can be calculated. Experiments are conducted to establish the relationship between the torsional stiffness and roughness parameters of the machined tooth surface. The effect of input torque on the torsional stiffness has also been analyzed. This study formulates a relationship between the torsional stiffness and surface characteristics of cycloid gears, which can help improve their design and manufacture in the future.

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