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
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;
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
DOI :
10.1109/ICICTA.2010.302