Robust Controller Design for a Generic Helicopter Model: An AI-Aided Application for Terrain Avoidance

Baris Baspinar*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper focuses on robust controller design for a generic helicopter model and terrain avoidance problem via artificial intelligence (AI). The helicopter model is presented as a hybrid system that covers hover and forward dynamics. By defining a set of easily accessible parameters, it can be used to simulate the motion of different helicopter types. A robust control structure based on reinforcement learning is proposed to ensure the system is robust against model parameter uncertainties. The developed generic model can be utilized in many helicopter applications that have been attempted to be solved with sampling-based algorithms or reinforcement learning approaches that take the dynamical constraints into consideration. This study also focuses on the helicopter terrain avoidance problem to illustrate how the model can be useful in these types of applications and provide an artificial intelligence-aided solution to terrain avoidance.

Original languageEnglish
Article number757
JournalAerospace
Volume10
Issue number9
DOIs
Publication statusPublished - Sept 2023

Bibliographical note

Publisher Copyright:
© 2023 by the author.

Keywords

  • AI-aided application
  • artificial intelligence
  • helicopter model
  • reinforcement learning
  • robust controller design
  • terrain avoidance

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