期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 65, 期 10, 页码 8112-8123出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2018.2803773
关键词
Adaptive control; finite time; robotic manipulator; parameter estimation; unknown kinematics and dynamics
资金
- National Nature Science Foundation [61473120, 61573174]
- Science and Technology Planning Project of Guangzhou [201607010006]
- State Key Laboratory of Robotics and System (HIT) [SKLRS-2017-KF-13]
- Fundamental Research Funds for the Central Universities [2017ZD057]
- Shenzhen Science and Technology Project [JCYJ20160229172341417]
For parameter identifications of robot systems, most existing works have focused on the estimation veracity, but few works of literature are concerned with the convergence speed. In this paper, we developed a robot control/identification scheme to identify the unknown robot kinematic and dynamic parameters with enhanced convergence rate. Superior to the traditional methods, the information of parameter estimation error was properly integrated into the proposed identification algorithm, such that enhanced estimation performance was achieved. Besides, the Newton-Euler (NE) method was used to build the robot dynamic model, where a singular value decomposition-based model reduction method was designed to remedy the potential singularity problems of the NE regressor. Moreover, an interval excitation condition was employed to relax the requirement of persistent excitation condition for the kinematic estimation. By using the Lyapunov synthesis, explicit analysis of the convergence rate of the tracking errors and the estimated parameters were performed. Simulation studies were conducted to show the accurate and fast convergence of the proposed finite-time (FT) identification algorithm based on a 7-DOF arm of Baxter robot.
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