Publications de Georgios Stathopoulos

An Inertial Parallel and Asynchronous Forward-Backward Iteration for Distributed Convex Optimization

Two characteristics that make convex decomposition algorithms attractive are simplicity of operations and generation of parallelizable structures. In principle, these schemes require that all coordinates update at the same time, i.e., they are synchronous ...

SPRINGER/PLENUM PUBLISHERS2019

Learning Proximal Operators with Gaussian Processes

Georgios Stathopoulos, Colin Neil Jones, Xuan Truong Nghiem

Several distributed-optimization setups involve a group of agents coordinated by a central entity (coordinator), altogether operating in a collaborative framework. In such environments, it is often common that the agents solve proximal minimization problem ...

IEEE2018

Supplementary material for the paper: A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method

Georgios Stathopoulos, Colin Neil Jones

2018

Distributed Optimization and Control using Operator Splitting Methods

Georgios Stathopoulos

The significant progress that has been made in recent years both in hardware implementations and in numerical computing has rendered real-time optimization-based control a viable option when it comes to advanced industrial applications. At the same time, t ...

EPFL2018

A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method

Georgios Stathopoulos, Colin Neil Jones

We propose a way to estimate the value function of a convex proximal minimization problem. The scheme constructs a convex set within which the optimizer resides and iteratively refines the set every time that the value function is sampled, namely every tim ...

2018

Solving the Infinite-horizon Constrained LQR Problem using Accelerated Dual Proximal Methods

Georgios Stathopoulos, Colin Neil Jones, Milan Korda

This work presents an algorithmic scheme for solving the infinite-time constrained linear quadratic regulation problem. We employ an accelerated version of a popular proximal gradient scheme, commonly known as the Forward-Backward Splitting (FBS), and prov ...

Institute of Electrical and Electronics Engineers2017

Real-Time Distributed Algorithms for Nonconvex Optimal Power Flow

Georgios Stathopoulos, Colin Neil Jones, Jean-Hubert Hours, Yuejiang Liu

The optimal power flow (OPF) problem, a fundamental problem in power systems, is generally nonconvex and computationally challenging for networks with an increasing number of smart devices and real-time control requirements. In this paper, we first investi ...

2017

Operator Splitting Methods in Control

Georgios Stathopoulos, Colin Neil Jones, Ye Pu, Harsh Ambarishkumar Shukla

2016

Constrained LQR Using Online Decomposition Techniques

Georgios Stathopoulos, Colin Neil Jones

This paper presents an algorithm to solve the infinite horizon constrained linear quadratic regulator (CLQR) problem using operator splitting methods. First, the CLQR problem is reformulated as a (finite-time) model predictive control (MPC) problem without ...

2016

Guaranteeing Input Tracking For Constrained Systems: Theory and Application to Demand Response

Georgios Stathopoulos, Colin Neil Jones, Tomasz Tadeusz Gorecki, Altug Bitlislioglu

A method for certifying exact input trackability for constrained discrete time linear systems is introduced in this paper. A signal is assumed to be drawn from a reference set and the system must track this signal with a linear combination of its inputs. U ...

2015

Solving the infinite-horizon constrained LQR problem using splitting techniques

Georgios Stathopoulos, Colin Neil Jones, Milan Korda

This paper presents a method to solve the constrained infinite-time linear quadratic regulator (LQR) problem. We use an operator splitting technique, namely the alternating minimization algorithm (AMA), to split the problem into an unconstrained LQR proble ...

Elsevier2014

Splitting methods in control

Georgios Stathopoulos, Colin Neil Jones, Ye Pu, Alexander Szücs

The need for optimal control of processes under a restricted amount of resources renders first order optimization methods a viable option. Although computationally cheap, these methods typically suffer from slow convergence rates. In this work we discuss t ...

IEEE2014

A hierarchical time-splitting approach for solving finite-time optimal control problems

Georgios Stathopoulos, Yang Wang

2013