Multimodel Design of Large Scale Systems With Multiple Decision Makers

The central theme of this thesis is multimodeling. It is concerned with modeling and control strategy interaction in a multimodel context. Realistic situations are studied, which allow the decision makers to use different simplified models of the system. Three different approaches to multimodeling are examined. Firstly, within the framework of multiparameter singular perturbations, we demonstrate the well-posedness of an a-priori selected multimodeling scheme, for a class of Nash and team problems. This establishes, in some sense, the "robustness" of this multimodeling scheme to a class of solution concepts and information patterns. Secondly, for a class of weakly-coupled Markov chains, we use a perturbational approach to develop an efficient algorithm for computing near-optimal incentive policies, which allows for multimodeling on the part of the decision makers. Finally, for a class of linear-quadratic problems, we use an input-output approach to restructure the problem, and choose appropriate admissible strategies which induce multimodel solutions.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Saksena, Vikram Raj

• Engineering, Electronics and Electrical

Identifier

(UMI)AAI8302979

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/69244