Introduction to the Asymptotic Analysis of Optimal Control Problems: A Parade of Examples

  • Peter I. Kogut
  • Günter R. Leugering
Part of the Systems & Control: Foundations & Applications book series (SCFA)


The main interest in this book is in mathematical models of optimal control problems (OCPs) that depend on some small parameter ε. In many mathematical problems, which come from natural or engineering sciences, industrial applications, or abstract mathematical questions all by themselves, some parameters appear (small or large, of geometric or constitutive origin, coming from approximation processes or discretization arguments) and make those control problems increasingly complex or degenerate. For instance, if we deal with OCPs on reticulated structures or perforated domains, this small parameter comes from the geometry of such domains. This dependence can be defined both by a regular and a singular occurrence of the parameter ε (the presence of ε-periodic coefficients, ε-periodically perforated zone of controls, quickly oscillating boundaries, etc.). In order to proceed with a mathematical description, we formulate the following parameterized OCP (OCP ε ), where ε is a small parameter:
$$(\mathrm{OCP}_{\varepsilon}):\qquad \min\left\{I_{\varepsilon}(u,y)\,:\ (u,y)\in \Xi_{\varepsilon}\right\},$$
(B 1)

\(I_{{\varepsilon}}:\mathbb{U}_{{\varepsilon}}\times \mathbb{Y}_{{\varepsilon}}\rightarrow \overline{\mathbb{R}}\) is a cost functional (CF ε ),

(B 2)

\(\mathbb{Y}_{{\varepsilon}}\) is a space of states,

(B 3)

\(\mathbb{U}_{{\varepsilon}}\) is a space of controls,

(B 4)

\(\Xi_{{\varepsilon}}\subset\left\{(u_{{\varepsilon}},y_{{\varepsilon}})\in \mathbb{U}_{{\varepsilon}}\times \mathbb{Y}_{{\varepsilon}}\ :\ u\in U_{{\varepsilon}}, I_{{\varepsilon}}(u,y)<+\infty\right\}\) is a set of all admissible pairs linked by some state equation (SE ε ).


Optimal Control Problem Limit Analysis Asymptotic Analysis Limit Problem Admissible Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Faculty of Mathematics and Mechanics, Department of Differential EquationsOles Honchar Dnipropetrovsk National UniversityDnipropetrovskUkraine
  2. 2.Department of Mathematics, Chair of Applied Mathematics IIFriedrich-Alexander Universität Erlangen-NürnbergErlangenGermany

Personalised recommendations