International audienceIn large-scale control optimization problems, a decentralized control structure can offer great scalability and rapidity advantages over a centralized implantation. Alternating Direction Method of Multipliers (ADMM) is a decentralized optimization algorithm which has the important benefit of being quite general in its scope and applicability in continuous systems. In this paper, a new projected ADMM algorithm is defined and it can work in hybrid systems. The key point is to add a convexification and a projection process during each iteration of ADMM algorithm. We have applied it to a charging control problem of electric vehicles. Simulation results show that the proposed algorithm can converge to a similar result as a ...
In this paper we propose an approach for solving convex quadratic programs (QPs) with lin-ear equali...
We propose a novel, system theoretic analysis of the Alternating Direction Method of Multipliers (AD...
The alternating direction method of multipliers (ADMM) is a benchmark for solving convex programming...
International audienceIn large-scale control optimization problems, a decentralized control structur...
The alternating direction method of multipliers (ADMM) is a first-order optimization algorithm for s...
In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for...
In this paper we propose an Alternating Direction Method of Multipliers (ADMM) algorithm for solving...
The alternating direction multiplier method (ADMM) was originally devised as an iterative method for...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/87...
A currently buzzing topic in the field of optimization is the analysis of the Alternating Direction ...
In this letter we demonstrate a novel alternating direction method of multipliers (ADMM) algorithm f...
This article details an investigation into the computational performance of algorithms used for solv...
Summarization: Lately, in engineering it has been necessary to develop algorithms that handle “big d...
The Alternating Direction Multipliers Method (ADMM) is a very popular algorithm for computing the so...
This paper presents a decentralized Model Predictive Control (MPC) for Plug-in Electric Vehicles (PE...
In this paper we propose an approach for solving convex quadratic programs (QPs) with lin-ear equali...
We propose a novel, system theoretic analysis of the Alternating Direction Method of Multipliers (AD...
The alternating direction method of multipliers (ADMM) is a benchmark for solving convex programming...
International audienceIn large-scale control optimization problems, a decentralized control structur...
The alternating direction method of multipliers (ADMM) is a first-order optimization algorithm for s...
In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for...
In this paper we propose an Alternating Direction Method of Multipliers (ADMM) algorithm for solving...
The alternating direction multiplier method (ADMM) was originally devised as an iterative method for...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/87...
A currently buzzing topic in the field of optimization is the analysis of the Alternating Direction ...
In this letter we demonstrate a novel alternating direction method of multipliers (ADMM) algorithm f...
This article details an investigation into the computational performance of algorithms used for solv...
Summarization: Lately, in engineering it has been necessary to develop algorithms that handle “big d...
The Alternating Direction Multipliers Method (ADMM) is a very popular algorithm for computing the so...
This paper presents a decentralized Model Predictive Control (MPC) for Plug-in Electric Vehicles (PE...
In this paper we propose an approach for solving convex quadratic programs (QPs) with lin-ear equali...
We propose a novel, system theoretic analysis of the Alternating Direction Method of Multipliers (AD...
The alternating direction method of multipliers (ADMM) is a benchmark for solving convex programming...