A switching control law for a networked visual servo control system

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2010

Without internal affiliation

  • Author: Wu, Haiyan

    Unknown

  • Author: Chen, Chih-Chung

    Institute of Automatic Control Engineering, Technische Universität München, Germany

  • Author: Feng, Juayun

    Institute of Automatic Control Engineering, Technische Universität München, Germany

  • Author: Kühnlenz, Kolja

    Institute of Automatic Control Engineering, Technische Universität München, Germany

  • Author: Hirche, Sandra

    Institute of Automatic Control Engineering, Technische Universität München, Germany

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In this paper, a novel switching controller is proposed for a networked visual servo control system with varying feedback delay due to image processing and data transmission. The varying image processing delay caused by the varying number of extracted features for pose estimation due to different view angles, illumination conditions and noise, is modeled by its occurrence probability. The time delay due to transmission over the communication network is also modeled as random process. By using a sampled-data system approach and an input-delay approach, the linearized visual servo control system is reformulated into a stochastic continuous-time system with time-varying delay. A novel stability condition and associated switching controller are derived based on the occurrence probabilities of delays. Experiments on a 1-DoF linear module equipped with a camera are conducted to validate the proposed approach. A non-switching controller approach is implemented for comparison. The experimental results demonstrate significant performance improvement of the proposed control approach.
Original languageEnglish
Title of host publicationIEEE International Conference on Robotics & Automation (ICRA)
PublisherIEEE
Publication date2010
Pages5556 - 5563
ISBN (print)9781424450381
DOIs
StatePublished

Conference

Conference2010 IEEE International Conference on Robotics and Automation
CountryUnited States
CityAnchorage, AK
Period03/05/1008/05/10
Internet addresshttp://icra2010.grasp.upenn.edu/
CitationsWeb of Science® Times Cited: No match on DOI
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