Analytical and Experimental Decentralized Adaptive Control of a High-Degrees-of-Freedom Robot Manipulator
Alexander Bertino, Peiman Naseradinmousavi, Atul Kelkar
- Year
- 2021
- Citations
- 10
Abstract
Abstract In this paper, we study the analytical and experimental control of a seven degrees-of-freedom (7DOF) robot manipulator. A model-free decentralized adaptive control strategy is presented for the tracking control of the manipulator. The problem formulation and experimental results demonstrate the computational efficiency and simplicity of the proposed method. The results presented here are one of the first known experiments on a redundant 7DOF robot. The efficacy of the adaptive decentralized controller is demonstrated experimentally by using the Baxter robot to track a desired trajectory. Simulation and experimental results clearly demonstrate the versatility, tracking performance, and computational efficiency of this method.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002