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Experimental Evaluation of an Explicit Model Predictive Controller for an Adhesion Vortex Actuated Climbing Robot
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-6415-6982
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-9399-7801
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2020 (English)In: 2020 American Control Conference (ACC), IEEE, 2020, p. 2137-2142Conference paper, Published paper (Refereed)
Abstract [en]

This article establishes an Explicit Model Predictive Control (EMPC) scheme for controlling the adhesion of a climbing Vortex Robot (VR). The VR utilizes an Electric Ducted Fan (EDF) as the Vortex Actuator (VA), where the dynamics have been identified via an Autoregressive-Moving-Average with eXternal input (ARMAX) identification scheme. An explicit controller via the use of a Constraint Finite Time Optimal Control (CFTOC) approach is designed in an offline manner and implemented for the case of the VR, where the adhesion reference is provided by a static force model. The presented approach results in a lookup table realization that ensures overall system stability in all state transitions, while being able to accurately control the adhesion force for arbitrary setup orientations. The efficacy of the proposed control scheme is demonstrated through experimental results involving a moving test surface under random inclinations and robot orientations.

Place, publisher, year, edition, pages
IEEE, 2020. p. 2137-2142
Series
American Control Conference (ACC), ISSN 0743-1619, E-ISSN 2378-5861
Keywords [en]
Adhesives, Force, Robot sensing systems, Force measurement, Inspection, Task analysis
National Category
Robotics and automation
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-77811DOI: 10.23919/ACC45564.2020.9147658ISI: 000618079802019Scopus ID: 2-s2.0-85089563907OAI: oai:DiVA.org:ltu-77811DiVA, id: diva2:1395424
Conference
2020 Americal Control Conference (ACC), 1-3 July, 2020, Denver, USA
Note

ISBN för värdpublikation: 978-1-5386-8266-1

Available from: 2020-02-21 Created: 2020-02-21 Last updated: 2025-02-09Bibliographically approved

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Papadimitriou, AndreasAndrikopoulos, GeorgiosNikolakopoulos, George

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