Incremental Nonlinear Control for Aircraft with Sensors Measurement Compensation

Yu Li, Xiaoxiong Liu, Ruichen Ming, Weiguo Zhang

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

1 Scopus citations

Abstract

To improve the robustness of the system, this paper utilizes the robust Incremental Nonlinear Dynamic Inversion (INDI) technique to design flight control law. Compared with the Nonlinear Dynamic Inversion (NDI), the INDI controller is no longer required the system model data except for the control effectiveness model, but needs additional angular acceleration signals. The angular accelerations are usually obtained by the differential method, which will inevitably introduce delays caused by filtering. Therefore, this paper also provides a solution to deal with measurement delays. Subsequently, the aircraft model with angular rates and sideslip angle is established, and the INDI-based controller is designed to enhance the flight control law. In addition, the compensator reduces the influence of the measurement delays, which prevents the aircraft from oscillation. Finally, the robustness of the designed flight control law and the effectiveness of the compensator are verified under the disturbance of parameters change, whose results demonstrate the theoretical analysis and meets the expected requirements.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages7689-7694
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • flight control law
  • Incremental Nonlinear Dynamic Inversion
  • measurement delays
  • robustness

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