DocumentCode :
2983896
Title :
Probabilistic Differential Evolution for optimal design of LQR weighting matrices
Author :
Liouane, Hend ; Chiha, Ibtissem ; Douik, Ali ; Messaoud, Hassani
Author_Institution :
Ecole Nat., d´´Ing. de Monastir, ATSI, Monastir, Tunisia
fYear :
2012
fDate :
2-4 July 2012
Firstpage :
18
Lastpage :
23
Abstract :
Recently, Differential Evolution algorithms come into play as they provide best tradeoffs between solution quality and the computational effort required for determining a satisfactory approximation of the optimised solution. In this paper, an optimal design of LQR weighting matrices using Probabilistic Differential Evolution algorithm for a constrained state feedback problem is presented. These weighting matrices are designed on the desired performance set by the designer. This method shows its efficiency in the proposed problem and can be considered as a competitive method for those issued from a complicate mathematic formulation. In fact, the results of simulation of an Aircraft Landing system show the effectiveness of the proposed method.
Keywords :
aircraft landing guidance; evolutionary computation; linear quadratic control; probability; state feedback; LQR weighting matrices; aircraft landing system simulation; competitive method; constrained state feedback problem; linear quadratic regulator; mathematic formulation; optimal design; probabilistic differential evolution algorithm; Aircraft; Algorithm design and analysis; Cost function; Mathematical model; Probabilistic logic; Vectors; LQR techniques; Probabilistic Differential Evolution algorithm; optimisation under constraints; weighting matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications (CIMSA), 2012 IEEE International Conference on
Conference_Location :
Tianjin
ISSN :
2159-1547
Print_ISBN :
978-1-4577-1778-9
Type :
conf
DOI :
10.1109/CIMSA.2012.6269612
Filename :
6269612
Link To Document :
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