期刊
INFORMATION SCIENCES
卷 420, 期 -, 页码 148-158出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2017.08.052
关键词
Planar underactuated manipulator; Genetic algorithm; Particle swarm optimization algorithm; Angle constraint
资金
- National Natural Science Foundation of China [61374106]
- Hubei Provincial Natural Science Foundation of China [2015CFA010]
- 111 project [B17040]
This paper presents a quick two-stage position control strategy based on a hybrid intelligent optimization algorithm for a planar n-link underactuated manipulator with a passive first joint. In stage 1, the system is directly reduced to a planar virtual Acrobot by controlling n-2 active links to their target angles. A hybrid intelligent optimization algorithm, which includes genetic algorithm (GA) and particle swarm optimization algorithm (PSO), is used to solve all link target angles according to the target position of the system. By coordinating GA and PSO, the hybrid intelligent optimization algorithm ensures that all link target angles, the angle of the passive link at the end of stage 1, and the initial angle of the active link of the planar virtual Acrobot meet the angle constraint of the planar virtual Acrobot. So, the position control objective of the planar n-link underactuated manipulator is realized by controlling the active link of the planar virtual Acrobot to its target angle in stage 2. (C) 2017 Elsevier Inc. All rights reserved.
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