Near optimal tracking solution for input constrained UAV using MPC

Eng Kee Poh, Jian Liang Wang, Keck Voon Ling

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

5 Citations (Scopus)

Abstract

In this paper, model predictive control (MPC) with cost function which is non-quadratic in control input is used to design a high level controller for fixed wing unmanned aerial vehicle (UAV). Given the kinematic model for UAV with low level autopilot, the control objective is to track straight lines defined by a set of way points. The path tracking problem is transformed to a problem of regulating the distance and heading error from desired straight lines. The optimization problem for MPC incorporates information on future paths. It is shown that under certain conditions the solution to MPC problem approaches the Dubins path. The simulation results also demonstrate that using our proposed scheme, the UAV follows the Dubins path.

Original languageEnglish
Title of host publicationAIAA Guidance, Navigation, and Control Conference
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventAIAA Guidance, Navigation, and Control Conference - Toronto, ON, Canada
Duration: 2 Aug 20105 Aug 2010

Publication series

NameAIAA Guidance, Navigation, and Control Conference

Conference

ConferenceAIAA Guidance, Navigation, and Control Conference
Country/TerritoryCanada
CityToronto, ON
Period2/08/105/08/10

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Systems Engineering

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