首页|Findings from Tongji University Update Knowledge of Robotics (Compound Control M ethod for Reliability of the Robotic Arms With Clearance Joint)
Findings from Tongji University Update Knowledge of Robotics (Compound Control M ethod for Reliability of the Robotic Arms With Clearance Joint)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting out of Shanghai, People's Republic o f China, by NewsRx editors, research stated, "This study provides a reliability improvement control method for robotic arms with clearance joints. Firstly, the dynamical model of a six-DOF robotic arm with joint clearance is established, an d the Archard model is utilized to describe joint wear, considering its effect o n clearance evolution." Funders for this research include National Natural Science Foundation of China ( NSFC), National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central Universities. Our news journalists obtained a quote from the research from Tongji University, "The kinematic and dynamic characteristics of the robotic arm with clearances ar e analyzed concerning the contact and operation state variations. Then, the infl uence of clearance wear on the operational reliability of the robotic arm is stu died as joint wear in the robotic arm contains interval uncertainty. To provide the uncertainty factors caused by the interval, we introduce Chebyshev functions to describe the dynamic response uncertainty and reliability. The non-probabili stic reliability index is given to evaluate the reliability of the robotic arm b ased on the stress intensity interference theory. Lastly, to improve operational accuracy and reliability, a novel compound control strategy containing collisio n force feedforward and PD feedback is carried out. It is compared with the trad itional PD control strategy. Also, the sensitivity and robustness of the propose d compound control strategies are discussed. The results show that the proposed control strategy can effectively enhance the dynamics precision and reliability of the robotic arm, with satisfactory robustness."
ShanghaiPeople's Republic of ChinaAs iaEmerging TechnologiesMachine LearningRoboticsRobotsTongji University
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