Piecewise constant model predictive control for autonomous helicopters

Cunjia Liu, Wen Hua Chen, John Andrews

Research output: Journal article publicationJournal articleAcademic researchpeer-review

32 Citations (Scopus)

Abstract

This paper introduces an optimisation based control framework for autonomous helicopters. The framework contains a high-level model predictive control (MPC) and a low-level linear controller. The proposed MPC works in a piecewise constant fashion to reduce the computation burden and to increase the time available for performing online optimisation. The linear feedback controller responds to fast dynamics of the helicopter and compensates the low bandwidth of the high-level controller. This configuration allows the computationally intensive algorithm applied on systems with fast dynamics. The stability issues of the high-level MPC and the overall control scheme are discussed. Simulations and flight tests on a small-scale helicopter are carried out to verify the proposed control scheme.

Original languageEnglish
Pages (from-to)571-579
Number of pages9
JournalRobotics and Autonomous Systems
Volume59
Issue number7-8
DOIs
Publication statusPublished - Jul 2011

Keywords

  • Autonomous flight
  • Flight test
  • Helicopter
  • Model predictive control
  • Stability

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • General Mathematics
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Piecewise constant model predictive control for autonomous helicopters'. Together they form a unique fingerprint.

Cite this