Disturbance observer-based motion control of small autonomous underwater vehicles

Bingheng Wang, Marko Mihalec, Yongbin Gong, Dario Pompili, Jingang Yi

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

Abstract

This paper presents a trajectory-tracking method using disturbance observer-based model predictive control (MPC) for small autonomous underwater vehicles (AUV). The goal of the work is to design a robust motion controller for AUVs under the system constraints and unknown disturbances such as hydrodynamics and ocean currents. Super-twisting-algorithm (STA) is employed to design the disturbance observer and its output is used and included in the feedback linearization law to compensate for the disturbances. The control inputs are generated using the MPC design with the nominal linearized model. Simulation results are included to validate the effectiveness of the control design and also compare with the traditional MPC motion control.

Original languageEnglish (US)
Title of host publicationModeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations
Subtitle of host publicationModeling, Analysis, and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791851913
DOIs
StatePublished - 2018
EventASME 2018 Dynamic Systems and Control Conference, DSCC 2018 - Atlanta, United States
Duration: Sep 30 2018Oct 3 2018

Publication series

NameASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Volume3

Other

OtherASME 2018 Dynamic Systems and Control Conference, DSCC 2018
Country/TerritoryUnited States
CityAtlanta
Period9/30/1810/3/18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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