Titlebook: Developments in Model-Based Optimization and Control; Distributed Control Sorin Olaru,Alexandra Grancharova,Fernando Lobo Pe Book 2015 Spr

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fidelity

incite

https://doi.org/10.1007/978-3-319-26687-9Bioprocesses; Constrained Estimation; Constrained and Predictive Control; Control of Impulsive Systems;

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Unsaturated-Fat

https://doi.org/10.1007/978-3-642-01546-5ex problems which can arise in real-time applications, such as model predictive control. When it is difficult to project on the primal constraint set described by a collection of general convex functions, we use the Lagrangian relaxation to handle the complicated constraints and then, we apply dual

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Willi Freeden,Michael Schreinerto be relevant in explicit model predictive control (MPC) design in terms of reducing the prediction horizon to at most two steps. In view of practical applications, typically leading to problems that are not directly invertible, we show how to adapt the inverse optimality to specific, possibly conv

山崩

Geodetic Boundary Value Problemnd input constraints is proposed. The robustness is defined in terms of the optimization of a cost function accumulated over the uncertainty and satisfying state constraints for a finite subset of uncertainties. The approach reformulates the original centralized robust MPC problem into a quadratic p

潛移默化

https://doi.org/10.1007/978-3-642-54551-1tems, typically considered as large-scale systems, can include different dynamical and functional characteristics in both, generators and loads. In this sense, the use of distributed-coordinated control strategies, including operational constraints, becomes an interesting alternative for these appli

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