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A combined genetic algorithms-shooting method approach to solving optimal control problems.

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Title: A combined genetic algorithms-shooting method approach to solving optimal control problems.
Authors: Sim, Y. C., Leng, S. B., Subramaniam, V.
Source: International Journal of Systems Science. Jan2000, Vol. 31 Issue 1, p83-89. 7p. 3 Diagrams, 1 Chart, 7 Graphs.
Subjects: Mathematical optimization, Automatic control systems, Boundary value problems
Abstract: In this paper, an alternative method for solving optimal control problems is presented. By applying calculus of variations, the optimal control problem can be reduced to solving a two-point boundary value problem. Here, the solution is generated with a combination of two methods genetic algorithms (GA) and the shooting method. An estimate of the optimal solution is first obtained using GA. This solution is in turn used as the initial guess for the shooting method. This combined method is applied to an optimal missile guidance problem. The performances of the combined method and GA are evaluated by simulation and compared. The results clearly show that the proposed combined method is able to locate the optimal solution more efficiently than GA. The results also show that the combined method never fails to correctly determine the optimal solution. Therefore, it proves to be more robust than the shooting method whose convergence is not always guaranteed. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 3810667
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: A combined genetic algorithms-shooting method approach to solving optimal control problems.
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  Data: <searchLink fieldCode="AR" term="%22Sim%2C+Y%2E+C%2E%22">Sim, Y. C.</searchLink><br /><searchLink fieldCode="AR" term="%22Leng%2C+S%2E+B%2E%22">Leng, S. B.</searchLink><br /><searchLink fieldCode="AR" term="%22Subramaniam%2C+V%2E%22">Subramaniam, V.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Systems+Science%22">International Journal of Systems Science</searchLink>. Jan2000, Vol. 31 Issue 1, p83-89. 7p. 3 Diagrams, 1 Chart, 7 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Automatic+control+systems%22">Automatic control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Boundary+value+problems%22">Boundary value problems</searchLink>
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  Data: In this paper, an alternative method for solving optimal control problems is presented. By applying calculus of variations, the optimal control problem can be reduced to solving a two-point boundary value problem. Here, the solution is generated with a combination of two methods genetic algorithms (GA) and the shooting method. An estimate of the optimal solution is first obtained using GA. This solution is in turn used as the initial guess for the shooting method. This combined method is applied to an optimal missile guidance problem. The performances of the combined method and GA are evaluated by simulation and compared. The results clearly show that the proposed combined method is able to locate the optimal solution more efficiently than GA. The results also show that the combined method never fails to correctly determine the optimal solution. Therefore, it proves to be more robust than the shooting method whose convergence is not always guaranteed. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Systems Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/002077200291488
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        Text: English
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      – SubjectFull: Automatic control systems
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      – SubjectFull: Boundary value problems
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      – TitleFull: A combined genetic algorithms-shooting method approach to solving optimal control problems.
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              Text: Jan2000
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