An adaptive trajectory tracking control of four rotor hover vehicle using extended normalized radial basis function network

Rooh ul Amin, Li Aijun, Muhammad Umer Khan, Shahaboddin Shamshirband, Amirrudin Kamsin

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.

Original languageEnglish
Pages (from-to)53-74
Number of pages22
JournalMechanical Systems and Signal Processing
Volume83
DOIs
StatePublished - 15 Jan 2017

Keywords

  • Adaptive neural network control
  • Extended normalized radial basis function
  • Four rotor hover vehicle
  • Unmodeled dynamics approximation

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