Distributed MPC with parametric coordination

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00306464" target="_blank" >RIV/68407700:21230/16:00306464 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ACC.2016.7526652" target="_blank" >http://dx.doi.org/10.1109/ACC.2016.7526652</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACC.2016.7526652" target="_blank" >10.1109/ACC.2016.7526652</a>

Result language
angličtina
Original language name
Distributed MPC with parametric coordination
Original language description
The paper presents an effective coordination scheme for a distributed optimization based on dual decomposition. The targeted class of optimization problems are strictly convex quadratic functions with linear constraints, where the dual function with coupling equality constraints in Lagrangian is continuous piecewise quadratic. The coordination is based on multi-parametric programming - the subproblem solvers return their solution on a polyhedron around a given Lagrange multiplier value. Centralized coordinator constructs the gradient and Hessian of a dual function and reaches exact consensus in a finite number of iterations, while only some subproblems are queried for a new solution in each iteration. The algorithm is applied to the distributed model predictive control. The efficiency, in terms of optimization time and the number of iterations, is demonstrated on the distributed model predictive control of the Barcelona water distribution network
Czech name
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Czech description
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Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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