Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 14, Issue 7, Pages 3044-3053Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2017.2766455
Keywords
Input-output information; Jacobian-matrix-adaption (JMA); robot manipulators; unknown models; zeroing dynamics
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Funding
- National Natural Science Foundation of China [61473323, 61401385]
- Science and Technology Program of Guangzhou, China [2014J4100057]
- Hong Kong Research Grants Council Early Career Scheme [25214015]
- Departmental General Research Fund of Hong Kong Polytechnic University [G.61.37.UA7L]
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Tracking control of robot manipulators is a fundamental and significant problem in robotic industry. As a conventional solution, the Jacobian-matrix-pseudo-inverse (JMPI) method suffers from two major limitations: one is the requirement on known information of the robot model such as parameter and structure; the other is the position error accumulation phenomenon caused by the open-loop nature. To overcome such two limitations, this paper proposes a novel Jacobian-matrix-adaption (JMA) method for the tracking control of robot manipulators via the zeroing dynamics. Unlike existing works requiring the information of the known robot model, the proposed JMA method uses only the input-output information to control the robot with unknown model. The solution based on the JMA method transforms the internal, implicit, and unmeasurable model information to the external, explicit, and measurable input-output information. Moreover, simulation studies including comparisons and tests substantiate the efficacy and superiority of the proposed JMA method for the tracking control of robot manipulators subject to unknown models.
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