Adaptive tracking control based on neural approximation for the yaw motion of a small-scale unmanned helicopter

Tri Quang Le, Ying-Chih Lai, Chun Liang Yeh

Research output: Contribution to journalArticle

Abstract

This article aims to study a solution that can solve the problem of tracking control for yaw motion of an unmanned helicopter. The non-affine nonlinear equation is converted to a simplified affine model. The unknown parameters are estimated by the Levenberg–Marquardt algorithm. An autonomous flight controller is developed with the Lyapunov-based adaptive controller for a discrete-time system. For flight data collection and verification purpose, the software-in-the-loop is constructed based on Simulink and X-Plane simulator. The designed system is applied in the control of the yaw motion of an R30 V2 helicopter under ideal and turbulent environments. The performance of the proposed method is compared with the fuzzy logic controller, and the simulation results show that the quality of the current approach is considerably better.

Original languageEnglish
JournalInternational Journal of Advanced Robotic Systems
Volume16
Issue number1
DOIs
Publication statusPublished - 2019 Jan 1

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Helicopters
Controllers
Nonlinear equations
Fuzzy logic
Simulators

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Artificial Intelligence

Cite this

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Adaptive tracking control based on neural approximation for the yaw motion of a small-scale unmanned helicopter. / Le, Tri Quang; Lai, Ying-Chih; Yeh, Chun Liang.

In: International Journal of Advanced Robotic Systems, Vol. 16, No. 1, 01.01.2019.

Research output: Contribution to journalArticle

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