Jose Maria Maestre

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This is a position paper on the current state of the art in distributed Model Predictive Control (M PC) and our view on its future potential. We present results from a recent survey of 3S distributed MPC approaches. For this, we propose a way in which distributed MPC approaches can be categorized for comparison. We also link the potential that these(More)
Open water systems are one of the most externally influenced systems due to their size and continuous exposure to uncertain meteorological forces. The control of systems under uncertainty is in general a challenging problem. In this paper we use a stochastic programming approach to control a drainage system in which the weather forecast is modeled as a(More)
Open water systems are one of the most externally influenced systems due to their size and continuous exposure to uncertain meteorological forces. In this paper we use a stochastic programming approach to control a drainage system in which the weather forecast is modeled as a disturbance tree. A model predictive controller is used to optimize the expected(More)
In this paper, a robust distributed model predictive control scheme is proposed for linear, time-invariant dynamically coupled systems. Uniquely, controllers optimize, and exchange information about, state and input sets, rather than planned state and control trajectories, in order to coordinate actions and reduce the effects of the mutual disturbances(More)