In this paper, optimal control for linear singular
system with quadratic performance is obtained using
genetic programming (GP). The goal is to provide
optimal control with reduced calculus effort by
comparing the solutions of the matrix Riccati
differential equation (MRDE), obtained from well known
traditional RungeKutta (RK) method and genetic
programming method. To obtain the optimal control, the
solution of MRDE is computed based on grammatical
evolution. Accuracy of the solution of the GP approach
to the problem is qualitatively better. An illustrative
numerical example is presented for the proposed
method.
%0 Journal Article
%1 Kumar:2007:AMC
%A Kumar, A. Vincent Antony
%A Balasubramaniam, P.
%D 2007
%J Applied Mathematics and Computation
%K Grammatical Linear Matrix Optimal Riccati RungeKutta algorithms, control, differential equation, evolution genetic method, programming, singular system,
%N 1
%P 78--89
%R doi:10.1016/j.amc.2007.02.122
%T Optimal control for linear singular system using
genetic programming
%V 192
%X In this paper, optimal control for linear singular
system with quadratic performance is obtained using
genetic programming (GP). The goal is to provide
optimal control with reduced calculus effort by
comparing the solutions of the matrix Riccati
differential equation (MRDE), obtained from well known
traditional RungeKutta (RK) method and genetic
programming method. To obtain the optimal control, the
solution of MRDE is computed based on grammatical
evolution. Accuracy of the solution of the GP approach
to the problem is qualitatively better. An illustrative
numerical example is presented for the proposed
method.
@article{Kumar:2007:AMC,
abstract = {In this paper, optimal control for linear singular
system with quadratic performance is obtained using
genetic programming (GP). The goal is to provide
optimal control with reduced calculus effort by
comparing the solutions of the matrix Riccati
differential equation (MRDE), obtained from well known
traditional RungeKutta (RK) method and genetic
programming method. To obtain the optimal control, the
solution of MRDE is computed based on grammatical
evolution. Accuracy of the solution of the GP approach
to the problem is qualitatively better. An illustrative
numerical example is presented for the proposed
method.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Kumar, A. Vincent Antony and Balasubramaniam, P.},
biburl = {https://www.bibsonomy.org/bibtex/2f2784a0a62963182b47b99b092c9cf86/brazovayeye},
doi = {doi:10.1016/j.amc.2007.02.122},
interhash = {330a774c51beac67452f8115bb60dbd9},
intrahash = {f2784a0a62963182b47b99b092c9cf86},
journal = {Applied Mathematics and Computation},
keywords = {Grammatical Linear Matrix Optimal Riccati RungeKutta algorithms, control, differential equation, evolution genetic method, programming, singular system,},
month = {1 September},
note = {Article in Press},
number = 1,
pages = {78--89},
timestamp = {2008-06-19T17:44:28.000+0200},
title = {Optimal control for linear singular system using
genetic programming},
volume = 192,
year = 2007
}