In this paper we present a distributed control approach for the multi-user multi-constrained waterfilling. This a specific category of distributed optimization for Networked Control Systems (NCSs), where agents aim at optimizing a non-separable global objective function while satisfying both local constraints and coupling constraints. Differently from the existing literature, in the considered setting we adopt a fully distributed mechanism where communication is allowed between neighbors only. First, we formulate a general multi-user waterfilling-structured optimization problem including coupling constraints, which may represent many engineering distributed control problems. Successively, we define a low-complexity iterative distributed algorithm based on duality, consensus and fixed point mapping theory. Finally, applying the technique to a simulated case referring to the electric vehicles optimal charging problem, we show its effectiveness.
Distributed Control for Waterfilling of Networked Control Systems with Coupling Constraints / Carli, Raffaele; Dotoli, Mariagrazia. - ELETTRONICO. - (2019), pp. 3710-3715. (Intervento presentato al convegno 57th IEEE Conference on Decision and Control, CDC 2018 tenutosi a Miami Beach, FL nel December 17-19, 2018) [10.1109/CDC.2018.8619425].
Distributed Control for Waterfilling of Networked Control Systems with Coupling Constraints
Raffaele Carli;Mariagrazia Dotoli
2019-01-01
Abstract
In this paper we present a distributed control approach for the multi-user multi-constrained waterfilling. This a specific category of distributed optimization for Networked Control Systems (NCSs), where agents aim at optimizing a non-separable global objective function while satisfying both local constraints and coupling constraints. Differently from the existing literature, in the considered setting we adopt a fully distributed mechanism where communication is allowed between neighbors only. First, we formulate a general multi-user waterfilling-structured optimization problem including coupling constraints, which may represent many engineering distributed control problems. Successively, we define a low-complexity iterative distributed algorithm based on duality, consensus and fixed point mapping theory. Finally, applying the technique to a simulated case referring to the electric vehicles optimal charging problem, we show its effectiveness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.