Hybrid acceleration/velocity-based disturbance observer for a quadrotor manipulation system

Ahmed Khalifa, Mohamed Fanni, Toru Namerikawa

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

1 Citation (Scopus)

Abstract

Aerial manipulation systems become very attractive for a wide range of applications due to their unique features. However, control of such system is quite challenging due to its high nonlinearities, couplings, and external disturbances. In this paper, a Disturbance Observer (DOb)-based linearization of a quadrotor manipulation system is utilized. The DOb estimates the disturbances and nonlinearities, then compensates them such that one can treat the control problem based on a simple linear control algorithm. However, the current developed DOb schemes in the literature are based on the precise measurement of the acceleration or the estimation of the velocity. Unlike, these methods, we propose a modified DOb, which is based on both the measured linear accelerations and angular velocities that can be obtained directly from the onboard Inertial Measurement Unit (IMU) and encoders. With this technique, the estimation of nonlinearities and disturbances are carried out without the need of estimation acceleration or velocity, and it is model free. The Effectiveness of the proposed technique is verified via numerical simulations.

Original languageEnglish
Title of host publication2016 IEEE Conference on Control Applications, CCA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages556-561
Number of pages6
ISBN (Electronic)9781509007554
DOIs
Publication statusPublished - 2016 Oct 10
Event2016 IEEE Conference on Control Applications, CCA 2016 - Buenos Aires, Argentina
Duration: 2016 Sep 192016 Sep 22

Publication series

Name2016 IEEE Conference on Control Applications, CCA 2016

Other

Other2016 IEEE Conference on Control Applications, CCA 2016
Country/TerritoryArgentina
CityBuenos Aires
Period16/9/1916/9/22

ASJC Scopus subject areas

  • Control and Optimization
  • Modelling and Simulation

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