Two-layer model predictive formation control of unmanned surface vehicle

Zhenyuans Fan, Huiping Li

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

11 Scopus citations

Abstract

This paper studies the model predictive formation control problems of unmanned surface vehicles (USVs). A two-layer model predictive control (MPC)-based formation control strategy is proposed. The proposed formation strategy artificially divides the model of each USV into two layers according to its kinematic model and dynamic model. Using the kinematic model, a distributed MPC algorithm is designed to ensure formation and coordination; with the generated command from the distributed MPC as tracking reference, an MPC is designed for the dynamic model to ensure optimal command tracking. Simulation and comparison studies show that the designed algorithm is computational more efficient in comparison with the centralized MPC formation algorithm.

Original languageEnglish
Title of host publicationProceedings - 2017 Chinese Automation Congress, CAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6002-6007
Number of pages6
ISBN (Electronic)9781538635247
DOIs
StatePublished - 29 Dec 2017
Event2017 Chinese Automation Congress, CAC 2017 - Jinan, China
Duration: 20 Oct 201722 Oct 2017

Publication series

NameProceedings - 2017 Chinese Automation Congress, CAC 2017
Volume2017-January

Conference

Conference2017 Chinese Automation Congress, CAC 2017
Country/TerritoryChina
CityJinan
Period20/10/1722/10/17

Keywords

  • Distributed model predictive control
  • Formation control
  • Unmanned surface vehicle

Fingerprint

Dive into the research topics of 'Two-layer model predictive formation control of unmanned surface vehicle'. Together they form a unique fingerprint.

Cite this