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A Probabilistic Algorithm for Optimal Control Problem

by Akbar Banitalebi, Mohd Ismail Abd Aziz, Rohanin Ahmad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 8
Year of Publication: 2012
Authors: Akbar Banitalebi, Mohd Ismail Abd Aziz, Rohanin Ahmad
10.5120/6932-9298

Akbar Banitalebi, Mohd Ismail Abd Aziz, Rohanin Ahmad . A Probabilistic Algorithm for Optimal Control Problem. International Journal of Computer Applications. 46, 8 ( May 2012), 48-55. DOI=10.5120/6932-9298

@article{ 10.5120/6932-9298,
author = { Akbar Banitalebi, Mohd Ismail Abd Aziz, Rohanin Ahmad },
title = { A Probabilistic Algorithm for Optimal Control Problem },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 8 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 48-55 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number8/6932-9298/ },
doi = { 10.5120/6932-9298 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:44.967211+05:30
%A Akbar Banitalebi
%A Mohd Ismail Abd Aziz
%A Rohanin Ahmad
%T A Probabilistic Algorithm for Optimal Control Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 8
%P 48-55
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we present a direct method for the numerical solution of the constrained optimal control problem when the gradient information is not available. At this aim, a new control parameterization based on Bernstein basis functions is suggested to convert control problem into nonlinear programing problem (NLP), and then a recently proposed stochastic algorithm called Probabilistic Global Search Johor (PGSJ) is considered for the solution of resultant NLP. The underlining idea of the PGSJ algorithm is to use probability density functions (PDF) to direct the search while no recombination operator is used. This algorithm along with the new Bernstein-based control parameterization (BCP) is compiled into BCP/PGSJ direct method to be applied to approximate the solution of the control problem up to the accuracy required. This method is lastly implemented while simulating some case studies which illustrate the efficiency of the method.

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Index Terms

Computer Science
Information Sciences

Keywords

Optimal Control Problem Constraints Direct Methods Stochastic Algorithm.

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