Derivative-free Kalman filtering-based control of prosthetic legs

  • S. Mahmoud Moosavi
  • , Seyed Abolfazl Fakoorian
  • , Vahid Azimi
  • , Hanz Richter
  • , Dan Simon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A derivative-free method for state estimation-based control of a robot/prosthesis system is presented. The system is the combination of a test robot that emulates human hip and thigh motion, and a powered transfemoral prosthetic leg. The robot/prosthesis combination is modeled as a three degree-of-freedom (DOF) robot: vertical hip displacement, thigh angle, and knee angle. We develop a derivative-free Kalman filter (DKF) for state estimation-based control for an n-DOF robotic system. We then propose a method to make the DKF robust when the robot dynamics include disturbances. In the robust DKF, we use two different methods for disturbance rejection: PD and PI. These disturbance compensators are used for supervisory control to make the DKF robust in the presence of disturbances. The simulation results show the advantages of the DKF and the robust DKF for the three-DOF robot/prosthesis system for state estimation-based control.
Original languageEnglish
Title of host publicationProceedings of the American Control Conference
Place of Publicationusa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5205-5210
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Conference

Conference2017 American Control Conference, ACC 2017
Country/TerritoryUnited States
CitySeattle
Period05/24/1705/26/17

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