Distributed Model Predictive Control with application to energy and transportation systems
The research program concerns with the problem of distributed control of large-scale systems, with many interacting heterogeneous components that are affected by stochastic uncertainty. The main objective is to develop distributed control techniques that allow to optimize a certain performance criterion, while satisfying various physical and/or technological constraints. According to the model predictive control strategy, a receding horizon implementation of the designed controller will allow for a better tuning of the control action based on the updated information on the system behavior. This will involve integrating filtering techniques in the distributed control scheme. The developed techniques will be tested on some examples pertaining to the energy and transportation systems domain.
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