Stewart Platform Manipulator: State Estimation Using Inertia Sensors and Unscented Kalman Filter

Shady A. Maged, A. A. Abouelsoud, Ahmed M R Fath El Bab, Toru Namerikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This manuscript presents the estimation of both position and velocity of Stewart manipulator using leg length measurements and MEMS inertial sensors. The estimation by using Unscented Kalman Filter (UKF) is based on the combination of different sensors. UKF is used as a nonlinear state estimator to the Stewart platform which is modeled as a stochastic differential equation due to measurement noise. The experimental results of the UKF are verified on the Stewart platform DELTALAB EX800 using LABVIEW real time software. The desired trajectories are compared with the estimated states (position and orientation) obtained using UKF. Moreover, the estimated leg lengths are compared with the real measured output from the potentiometer sensors of the six legs of the parallel manipulator. The experimental results show that the estimation error is bounded with small bound depending on the covariance matrices. This proves the effectiveness of the proposed Unscented Kalman Filter (UKF) as a nonlinear estimator with integration between inertial sensors and leg potentiometers.

Original languageEnglish
Title of host publicationProceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1136-1140
Number of pages5
ISBN (Electronic)9781509025350
DOIs
Publication statusPublished - 2016 Oct 31
Event3rd International Conference on Information Science and Control Engineering, ICISCE 2016 - Beijing, China
Duration: 2016 Jul 82016 Jul 10

Other

Other3rd International Conference on Information Science and Control Engineering, ICISCE 2016
CountryChina
CityBeijing
Period16/7/816/7/10

Keywords

  • Experimental results
  • MEMS inertial sensors
  • Stewart manipulator
  • UKF

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Maged, S. A., Abouelsoud, A. A., Bab, A. M. R. F. E., & Namerikawa, T. (2016). Stewart Platform Manipulator: State Estimation Using Inertia Sensors and Unscented Kalman Filter. In Proceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016 (pp. 1136-1140). [7726341] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICISCE.2016.244