Frequency-Domain System Identification of an Unmanned Helicopter Based on an Adaptive Genetic Algorithm

Author

Yuhu Du ; Jiancheng Fang ; Cunxiao Miao

Author_Institution

Sci. & Technol. on Inertial Lab., Beihang Univ., Beijing, China

Volume

61

Issue

2

fYear

2014

fDate

Feb. 2014

Firstpage

870

Lastpage

881

Abstract

This paper presents a frequency-domain identification method for an unmanned helicopter (UH) based on an adaptive genetic algorithm (AGA). By using a homemade micro-guidance, navigation, and control system (MGNCS), data regarding the inputs (control signals of servos) and outputs (states of the UH) are recorded. After data preprocessing, the attitude model of the UH is identified by employing the AGA. The identified model is then analyzed in the time domain and the frequency domain in comparison with the least squares (LS) method. Control compensators are designed based on the identified model. Automatic hovering is successfully achieved based on the compensators. Simulation and experimental results demonstrate the effectiveness and superiority of this identification method.

Keywords

attitude control; autonomous aerial vehicles; compensation; control system synthesis; genetic algorithms; helicopters; least squares approximations; mobile robots; AGA; MGNCS; UH attitude model; adaptive genetic algorithm; automatic hovering; control compensator design; frequency domain; frequency-domain system identification method; least squares method; microguidance-navigation-and-control system; time domain; unmanned helicopter; Adaptive genetic algorithm (AGA); least squares (LS); system identification; unmanned helicopter (UH);

fLanguage

English

Journal_Title

Industrial Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0278-0046

Type

jour

DOI

10.1109/TIE.2013.2257135

Filename

6494625