Affiliation:
1. College of Systems Engineering National University of Defense Technology Changsha 410073 China
2. School of Intelligence Science and Technology The Institute of Artificial Intelligence and the Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing 100083 China
3. School of Computer Science and Engineering Beijing Technology and Business University Beijing 100080 China
Abstract
AbstractIn the article, an event‐triggered control policy is developed for a robotic manipulator with flexible joint (RMFJ) in the presence of finite‐time convergence under the requirement of output constraints. Due to the vibration existing in the flexible joint, compared with the rigid manipulator, it is exceedingly difficult for RMFJ to design an adaptive method for realizing highly accurate control. In order to reduce and restrain the vibration of the flexible joint, a finite‐time convergence policy is designed by introducing the fractional order term. Moreover, the angular displacements of the link are constrained in the predefined region by using the Barrier function, which further enhances the operation safety. Neural networks learning is used to approximate unknown model parameters. Event‐trigger design is used to reduce the communication burden.
Funder
National Natural Science Foundation of China
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering
Cited by
5 articles.
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