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Conference Paper: Model and control for four-powered-caster vehicle: A probability-based approach

TitleModel and control for four-powered-caster vehicle: A probability-based approach
Authors
Keywordsprobability-based
holonomic
Dynamics control
mobile manipulator
Issue Date2013
Citation
Transactions of the Institute of Measurement and Control, 2013, v. 35, n. 7, p. 875-882 How to Cite?
AbstractA vehicle with four powered caster wheels can provide much more motion flexibility in a constrained environment. However, the dynamic modelling and control of such system is challenging due to its high redundancy. This paper investigates the dynamic model and tracking control for a four-powered-caster vehicle (4-PCV) on complex terrain without any additional sensor. The torques applied to the wheels are dynamically redistributed based on the real-time conditions of the whole wheel-ground interactions so that the vehicle can track the desired trajectory when moving on different terrains. A dynamic model considering the wheel-ground interaction is first derived. Then a novel approach based on a probability scheme is proposed to identify the status of the vehicle and the wheel slip ratio by only observing the velocity feedback from motors encoders. Based on this real-time perception information, a tracking controller and a torque distribution scheme are applied to make sure that each wheel can be self-adapted to meet a complex wheel-ground condition to eliminate or reduce the probability of slippage. The effectiveness of the proposed estimation approach and the performance of the torque distribution schemes are verified by simulation. © The Author(s) 2012.
Persistent Identifierhttp://hdl.handle.net/10722/213358
ISSN
2023 Impact Factor: 1.7
2023 SCImago Journal Rankings: 0.478
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Yong-
dc.contributor.authorJia, Yunyi-
dc.contributor.authorXi, Ning-
dc.date.accessioned2015-07-28T04:07:00Z-
dc.date.available2015-07-28T04:07:00Z-
dc.date.issued2013-
dc.identifier.citationTransactions of the Institute of Measurement and Control, 2013, v. 35, n. 7, p. 875-882-
dc.identifier.issn0142-3312-
dc.identifier.urihttp://hdl.handle.net/10722/213358-
dc.description.abstractA vehicle with four powered caster wheels can provide much more motion flexibility in a constrained environment. However, the dynamic modelling and control of such system is challenging due to its high redundancy. This paper investigates the dynamic model and tracking control for a four-powered-caster vehicle (4-PCV) on complex terrain without any additional sensor. The torques applied to the wheels are dynamically redistributed based on the real-time conditions of the whole wheel-ground interactions so that the vehicle can track the desired trajectory when moving on different terrains. A dynamic model considering the wheel-ground interaction is first derived. Then a novel approach based on a probability scheme is proposed to identify the status of the vehicle and the wheel slip ratio by only observing the velocity feedback from motors encoders. Based on this real-time perception information, a tracking controller and a torque distribution scheme are applied to make sure that each wheel can be self-adapted to meet a complex wheel-ground condition to eliminate or reduce the probability of slippage. The effectiveness of the proposed estimation approach and the performance of the torque distribution schemes are verified by simulation. © The Author(s) 2012.-
dc.languageeng-
dc.relation.ispartofTransactions of the Institute of Measurement and Control-
dc.subjectprobability-based-
dc.subjectholonomic-
dc.subjectDynamics control-
dc.subjectmobile manipulator-
dc.titleModel and control for four-powered-caster vehicle: A probability-based approach-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1177/0142331212445499-
dc.identifier.scopuseid_2-s2.0-84884178700-
dc.identifier.volume35-
dc.identifier.issue7-
dc.identifier.spage875-
dc.identifier.epage882-
dc.identifier.isiWOS:000326173800003-
dc.identifier.issnl0142-3312-

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