Optimization techniques for solving elliptic control problems with control and state constraints. Part 2: Distributed control

被引:25
作者
Maurer, H
Mittelmann, HD
机构
[1] Univ Munster, Inst Numer & Instrumentelle Math, D-48149 Munster, Germany
[2] Arizona State Univ, Dept Math, Tempe, AZ 85287 USA
关键词
elliptic control problems; distributed control; control and state constraints; discretization techniques; NLP-methods;
D O I
10.1023/A:1008774521095
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Part 2 continues the study of optimization techniques for elliptic control problems subject to control and state constraints and is devoted to distributed control. Boundary conditions are of mixed Dirichlet and Neumann type. Necessary conditions of optimality are formally stated in form of a local Pontryagin minimum principle, By introducing suitable discretization schemes, the control problem is transcribed into a nonlinear programming problem. The problems are formulated as AMPL (R. Fourer, D.M. Gay, and B.W. Kernighan, "AMPL: A modeling Language for Mathematical Programming", Duxbury Press, Brooks-Cole Publishing Company, 1993) scripts and several optimization codes are applied. In particular it is shown that a recently developed interior point method is able to solve theses problems even for high discretizations. Several numerical examples with Dirichlet and Neumann boundary conditions are provided that illustrate the performance of the algorithm for different types of controls including bang-bang controls, The necessary conditions of optimality are checked numerically in the presence of active control and state constraints.
引用
收藏
页码:141 / 160
页数:20
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