首页|Study Results from Shanghai Jiao Tong University Broaden Understanding of Robotics (A Variable Structure Passivity Control Method for Elastic Joint Robots Based On Cascaded High-order State Estimation)
Study Results from Shanghai Jiao Tong University Broaden Understanding of Robotics (A Variable Structure Passivity Control Method for Elastic Joint Robots Based On Cascaded High-order State Estimation)
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Data detailed on Robotics have been presented. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Passivity-based controllers are widely used to facilitate physical interaction between humans and elastic joint robots, as they enhance the stability of the interaction system. However, the joint position tracking performance can be limited by the structures of these controllers when the system is faced with uncertainties and rough high-order system state measurements (such as joint accelerations and jerks).” Financial support for this research came from National Natural Science Foundation of China (NSFC). Our news editors obtained a quote from the research from Shanghai Jiao Tong University, “This study presents a variable structure passivity (VSP) control method for joint position tracking of elastic joint robots, which combines the advantages of passive control and variable structure control. This method ensures the tracking error converges in a finite time, even when the system faces uncertainties. The method also preserves the passivity of the system. Moreover, a cascaded observer, called CHOSSO, is also proposed to accurately estimate high-order system states, relying only on position and velocity signals. This observer allows independent implementation of disturbance compensation in the acceleration and jerk estimation channels. In particular, the observer has an enhanced ability to handle fast time-varying disturbances in physical human-robot interaction.”
ShanghaiPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsShanghai Jiao Tong University
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Science Press
