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Modified shuffled frog leaping algorithm for optimization of UAV flight controller

Huangzhong Pu (College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China)
Ziyang Zhen (College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China)
Daobo Wang (College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, People's Republic of China)

International Journal of Intelligent Computing and Cybernetics

ISSN: 1756-378X

Article publication date: 29 March 2011

386

Abstract

Purpose

Attitude control of unmanned aerial vehicle (UAV) is the purposeful manipulation of controllable external forces to establish a desired attitude, which is inner‐loop of the autonomous flight control system. In the practical applications, classical control methods such as proportional‐integral‐derivative control are usually selected because of simple and high reliability. However, it is usually difficult to select or optimize the control parameters. The purpose of this paper is to investigate an intelligent algorithm based classical controller of UAV.

Design/methodology/approach

Among the many intelligent algorithms, shuffled frog leaping algorithm (SFLA) combines the benefits of the genetic‐based memetic algorithm as well as social behavior based particle swarm optimization. SFLA is a population based meta‐heuristic intelligent optimization method inspired by natural memetics. In order to improve the performance of SFLA, a different dividing method of the memeplexes is presented to make their performance balance; moreover, an evolution mechanism of the best frog is introduced to make the algorithm jump out the local optimum. The modified SFLA is applied to the tuning of the proportional coefficients of pitching and rolling channels of UAV flight control system.

Findings

Simulation of a UAV control system in which the nonlinear model is obtained by the wind tunnel experiment show the rapid dynamic response and high control precision by using the modified SFLA optimized attitude controller, which is better than that of the original SFLA and particle swarm optimization method.

Originality/value

A modification scheme is presented to improve the global searching capability of SFLA. The modified SFLA based intelligent determination method of the UAV flight controller parameters is proposed, in order to improve the attitude control performance of UAV.

Keywords

Citation

Pu, H., Zhen, Z. and Wang, D. (2011), "Modified shuffled frog leaping algorithm for optimization of UAV flight controller", International Journal of Intelligent Computing and Cybernetics, Vol. 4 No. 1, pp. 25-39. https://doi.org/10.1108/17563781111115778

Publisher

:

Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited

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