Automatic EKF tuning for UAS path following in turbulent air

Caterina Grillo, Fernando Montano

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

By using two simultaneously working Extended Kalman Filters, a procedure is implemented in order to perform in a fully autonomous way the path following in turbulent air. To guarantee the robustness of the proposed algorithm, an automatic tuning procedure is proposed to determine optimal values of Process and Measurement Noise statistics. Such a procedure is based on both the characteristics of the disturbances and the desired flight path; in particular, a specific performance index is applied to tune filters. In this way control laws are adapted to the flight condition and these lead to an optimal path-following. This research represents an upload of previous papers. It allows eliminating the time expensive trial and error procedure usually employed to tune Extended Kalman Filters. Obviously, procedure results are optimal for ever flight condition.
Original languageEnglish
Pages (from-to)241-246
Number of pages6
JournalInternational Review of Aerospace Engineering
Volume11
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Aerospace Engineering
  • Fluid Flow and Transfer Processes
  • Electrical and Electronic Engineering

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