Publications de Colin Neil Jones

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Receding horizon control requires the solution of an optimization problem at every sampling instant. We present efficient interior point methods tailored to convex multistage problems, a problem class which most relevant MPC problems with linear dynamics c ...

This paper considers linear discrete-time systems with additive bounded disturbances subject to hard control input bounds and constraints on the expected number of state-constraint violations averaged over time, or, equivalently, constraints on the probabi ...

This paper presents a Model Predictive Control (MPC) scheme for nonlinear continuous time systems where an extra performance index, which is not a measure of the distance to the set point, is introduced to influence the transient behavior of the controlled ...

This paper presents a distributed optimization algorithm tailored for solving optimal control problems arising in multi-building coordination. The buildings coordinated by a grid operator, join a demand response program to balance the voltage surge by usin ...

Linear quadratic model predictive control (MPC) with input constraints leads to an optimization problem that has to be solved at every instant in time. Although there exists computational complexity analysis for current online optimization methods dedicate ...

This paper deals with stochastic model predictive control of constrained discrete-time periodic linear systems. Control inputs are subject to periodically time-varying polytopic constraints with possibly time-dependent state and input dimensions. A stochas ...

This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances. A primal- ...

This paper examines the computational complexity certification of the fast gradient method for the solution of the dual of a parametric con- vex program. To this end, a lower iteration bound is derived such that for all parameters from a compact set a solu ...

This paper presents a solution method for parametric linear complementarity problems (PLCP) that relies on an enumeration technique to discover all feasible bases. The enumeration procedure is based on evaluating all possible combinations of active constra ...

This work presents an approach for both dis- tributed synthesis and control for a network of discrete-time constrained linear systems without central coordinator. Every system in the network is dynamically coupled to a number of neighboring systems and it ...

This paper investigates the relations between three different properties, which are of importance in optimal control problems: dissipativity of the underlying dynamics with respect to a specific supply rate, optimal operation at steady state, and the turnp ...

We characterize the maximum controlled invariant (MCI) set for discrete- as well as continuous-time nonlinear dynamical systems as the solution of an infinite-dimensional linear programming problem. For systems with polynomial dynamics and compact semialge ...

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 ...

This paper presents a Model Predictive Control (MPC) scheme for nonlinear continuous-time systems where an economic stage cost, which is not a measure of the distance to a desired set point, is combined with a classic stabilizing stage cost. The associated ...

High-speed applications impose a hard real-time constraint on the solution of a model predictive control (MPC) problem, which generally prevents the computation of the optimal control input. As a result, in most MPC implementations guarantees on feasibilit ...

A novel trust region method for solving linearly constrained nonlinear programs is presented. The proposed technique is amenable to a distributed implementation, as its salient ingredient is an alternating projected gradient sweep in place of the Cauchy po ...

In this study, we investigate the maximum possible profit for a commercial office building participating in New York’s Day-Ahead Demand Response (DADR) program. We formulate an optimal control problem, assuming perfect knowledge of future weather, occupanc ...

Federated learning (FL) is a promising learning paradigm that can tackle the increasingly prominent isolated data islands problem while keeping users' data locally with privacy and security guarantees. However, FL could result in task-oriented data traffic ...

This paper presents a method to analyze the technical and economic potential of combining different types of resources to provide grid services, with a particular focus on battery systems. The paper proposes a modelling paradigm where resources are describ ...

This paper addresses the design of Model Predictive Control (MPC) laws to solve the trajectory-tracking problem and the path-following problem for constrained under-actuated vehicles. By allowing an arbitrarily small asymptotic tracking error, we derive MP ...

Colin Neil Jones

Chattez avec Graph Search

Efficient Interior Point Methods for Multistage Problems Arising in Receding Horizon Control

Stochastic Model Predictive Control: Controlling the Average Number of Constraint Violations

A Model Predictive Control Scheme with Additional Performance Index for Transient Behavior

Distributed Multi-Building Coordination for Demand Response

Real-time input-constrained MPC using fast gradient methods

Stochastic MPC for Controlling the Average Constraint Violation for Periodic Linear System with Additive Disturbance

Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

Certification Aspects of the Fast Gradient Method for Solving the Dual of Parametric Convex Programs

Enumeration-based approach to solving parametric linear complementarity problems

Distributed Synthesis and Control of Constrained Linear Systems

On turnpike and dissipativity properties of continuous-time optimal control problems

Convex computation of the maximum controlled invariant set for polynomial control systems

Real-Time Distributed Algorithms for Nonconvex Optimal Power Flow

A Model Predictive Control scheme with Ultimate Bound for Economic Optimization

On real-time robust model predictive control

An Alternating Trust Region Algorithm for Distributed Linearly Constrained Nonlinear Programs, Application to the Optimal Power Flow Problem

Model Predictive Control for Market-Based Demand Response Participation

Over-the-Air Federated Learning via Second-Order Optimization

Economic study of the participation of multiple energy resources in grid services markets

Trajectory-tracking and Path-following Controllers for Constrained Underactuated Vehicles using Model Predictive Control