Dynamic Modeling and Analysis for 6-DOF Industrial Robots

Li, Yingjie; Na, Jing; Gao, Guanbin

doi:10.1109/ddcls49620.2020.9275052

Cited by 3 publications

(2 citation statements)

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“…Remark 1: Equation ( 1) is a dynamical model of a complex system established by the Lagrange method. However, as the number of series joints increase, the computational burden of the computer soars exponentially [4]. Based on this, the model is simplified that the center of mass of the connecting rod coincides with the geometric center and the calculation error is neglected.…”

Section: System Modeling and Problem Formulation 21 Dynamic Modeling ...mentioning

confidence: 99%

“…Considerable studies are executed to obtain a reasonable easy-to-control dynamic model of robot-assisted bathing. Newton Euler method [4] and Lagrange method [5] is widely applied to dynamic modeling where its main idea is based on balance of force and conservation of energy respectively. Nonetheless, the above modelling approach only yields a static model while the dynamic changes are not taken into account brought about by human-machine interaction (HMI) torque and external disturbances.…”

Section: Introductionmentioning

confidence: 99%

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Impedance Iterative Learning Sliding Mode Control for Robot-Assisted Bathing with Non-repetitive Trajectory

Guo

zhang

et al. 2022

Preprint

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In this paper, an impedance iterative learning sliding mode control (IILSMC) scheme for robot-assisted bathing with unknown model parameters is investigated. Firstly, impedance control is not only applied to adjust the desired trajectory, but also implemented to ensure the active compliance control of the robot-assisted bathing. Furthermore, iterative learning control is designed to dynamically estimate the unknown model parameters. To release the identical initial condition of iterative learning control (ILC), the trajectory reconstruction method is proposed, such that the convergence of tracking errors can be guaranteed with random initial status. Moreover, adaptive sliding mode control (SMC) is proposed where non-parametric, external disturbances and the human-machine interaction (HMI) torque generated during the bathing process is suppressed by adaptive method. Based on the composite energy function (CEF) method, the convergence of the double closed-loop system in the time domain and iterative domain is proved. Finally, through co-simulation of MATLAB/Simulink and ADAMS, the effectiveness and superiority of the control strategy proposed in this paper is jointly verified.

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Section: System Modeling and Problem Formulation 21 Dynamic Modeling ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%