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Large-Scale Optimization for Distributed Control

This PhD project investigate network topology such as hierarchical network structure, e.g. chordal graphs, for scalable computations with applications to control in a wide sense, e.g. system identification, machine learning, control design, and estimation

OptimizationChordal graph with associated clique tree for distributed computationsWe also study how privacy affects the achievable performance and what amount of communication that is needed between different computational agents in order to achieve the most efficient overall computations.

Different type of computational platforms will be investigated. We also also develop efficient optimization code for generic problem formulations.

Relevant applications are within infrastructure networks for traffic, water, gas, electricity, and building control.


Researchers

Photo of Anders Hansson

Anders Hansson

Professor

WASP research in optimization

Anders Hansson

Autonomous Optimization

We are investigating whether it is possible to use algorithms within machine learning to discover new optimization algorithms that function better than the current ones, which are constructed manually.
Shervin Parvini and Anders Hansson

WASP Optimization for Learning and Autonomy

Within the WASP research environment Optimization for Learning and Autonomy within the Division of Automatic Control we work with both development and applications of optimization.

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