Titlebook: Distributed Model Predictive Control Made Easy; José M. Maestre,Rudy R. Negenborn Book 2014 Springer Science+Business Media Dordrecht 2014

出價(jià)

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Distributed Optimization for MPC of Linear Dynamic Networksre influenced by the control signals of the upstream subsystems with constraints on state and control variables. A distributed gradient-based algorithm is presented for implementing an interior-point method distributively with a network of agents, one for each subsystem.

記憶法

CREEK

出來(lái)

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A Distributed Reference Management Scheme in Presence of Non-Convex Constraints: An MPC Based ApproaG) strategy is here proposed to coordinate a set of dynamically decoupled subsystems. The approach results in a receding horizon strategy that requires the computation of mixed-integer optimization programs.

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騷動(dòng)

978-94-024-0714-3Springer Science+Business Media Dordrecht 2014

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EVEN

https://doi.org/10.1057/9780230252998ynamical systems coupled by linear global constraints. The resulting structure is composed of one optimization agent for each system, and another one that has to ensure that the global constraints are fulfilled. The global solution of the problem is found in a finite number of iterations.