MINIMAX PROBLEMS FOR ENSEMBLES OF CONTROL-AFFINE SYSTEMS

被引:0
|
作者
Scagliotti, Alessandro [1 ,2 ]
机构
[1] Tech Univ Munich, CIT Sch, Boltzmannstr 3-II, D-85748 Garching, Germany
[2] Munich Ctr Machine Learning MCML, Munich, Germany
关键词
simultaneous control; minimax optimal control; Gamma-convergence; Pontryagin Maxi- mum Principle; CONVERGENCE;
D O I
10.1137/24M167531X
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we consider ensembles of control-affine systems in IIBd, and we study simultaneous optimal control problems related to the worst-case minimization. After proving that such problems admit solutions, denoting with (\ThetaN)N a sequence of compact sets that parametrize the ensembles of systems, we first show that the corresponding minimax optimal control problems are \Gamma-convergent whenever (\ThetaN)N has a limit with respect to the Hausdorff distance. Besides its independent interest, the previous result plays a crucial role for establishing the Pontryagin Maximum Principle (PMP) when the ensemble is parametrized by a set \Theta consisting of infinitely many points. Namely, we first approximate \Theta by finite and increasing-in-size sets (\ThetaN)N for which the PMP is known, and then we derive the PMP for the \Gamma-limiting problem. The same strategy can be pursued in applications, where we can reduce infinite ensembles to finite ones to compute the minimizers numerically. We bring as a numerical example the Schro"\dinger equation for a qubit with uncertain resonance frequency.
引用
收藏
页码:502 / 523
页数:22
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