Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories

Imraan A. Faruque*, Florian T. Muijres, Kenneth M. Macfarlane, Andrew Kehlenbeck, J.S. Humbert

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

This paper presents “optimal identification,” a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.
Original languageEnglish
Pages (from-to)165-179
JournalBiological Cybernetics
Volume112
Issue number3
Early online date3 Jan 2018
DOIs
Publication statusPublished - Jun 2018

Keywords

  • Control
  • Drosophila
  • Flight
  • Identification
  • Insect
  • Optimal

Fingerprint Dive into the research topics of 'Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories'. Together they form a unique fingerprint.

Cite this