期刊
PLOS ONE
卷 10, 期 6, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0129281
关键词
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资金
- Engineering and Physical Sciences Research Council (EPSRC) [EP/L026856/1, EP/J004561/1]
- National Natural Science Foundation of China (NSFC) [61473120, 61473038]
- Guangdong Provincial Natural Science Foundation of China [2014A030313266]
- European Commission [FP7-ICT-601003]
- EPSRC [EP/L026856/1, EP/J004561/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/J004561/1, EP/L026856/1] Funding Source: researchfish
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
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