DocumentCode
3206444
Title
LQG/LTR Flight Controller Optimal Design Based on Differential Evolution Algorithm
Author
Zhang, Meng ; Sun, Peiyong ; Cao, Ruiting ; Zhu, Jiangle
Author_Institution
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Volume
2
fYear
2010
fDate
11-12 May 2010
Firstpage
613
Lastpage
616
Abstract
In conventional Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) controller design, the designer should experiment with four different weighting matrices by trial-and-error method in order to get the flying quality requirement and the robustness. This method is a time consuming, inefficient and non-optimal method. To solve this problem, a LQG/LTR flight controller optimal design method based on differential evolution algorithm is proposed in this paper. In the optimal design, a Kalman filter is optimal designed by optimizing two weighting matrices based on a reference model and differential evolution algorithm firstly. So the optimal target feedback loop which satisfies the performance requirement is obtained. Secondly, the principle of the aircraft equivalent system analog match is used for reference to design an optimal state feedback gain matrix by optimizing another two weighting matrices. To validate the effect of this optimal design method, a longitudinal LQG/LTR flight controller is optimal designed based on differential evolution algorithm. The simulation results show the high effectiveness of this optimal design method.
Keywords
Kalman filters; aircraft control; control system synthesis; feedback; linear quadratic Gaussian control; multivariable control systems; optimal control; robust control; Kalman filter; LQG-LTR flight controller optimal design; aircraft equivalent system analog match; differential evolution algorithm; flying quality requirement; linear quadratic Gaussian-loop transfer recovery controller design; optimal state feedback gain matrix; optimal target feedback loop; robustness; trial-and-error method; weighting matrices; Aircraft; Algorithm design and analysis; Automatic control; Design automation; Design methodology; Design optimization; Evolutionary computation; Genetic algorithms; Optimal control; Robust control; LQG/LTR; differential evolution algorithm; flight controller; optimal design; weighting matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-7279-6
Electronic_ISBN
978-1-4244-7280-2
Type
conf
DOI
10.1109/ICICTA.2010.302
Filename
5523406
Link To Document