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Colin Neil Jones

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Related publications (242)

Page 2 of 13

Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Regression Approach

Colin Neil Jones, Emilio Maddalena

We propose a non-parametric regression methodology that enforces the regressor to be fully consistent with the sample set and the ground-truth regularity assumptions. As opposed to the Nonlinear Set Membership technique, this constraint guarantees the atta ...

ELSEVIER2020

Model predictive control of linear periodic systems - a unified framework including control of multirate and multiplexed systems

Colin Neil Jones

State-feedback model predictive control (MPC) of discrete-time linear periodic systems with possibly time-dependent state and control input dimension is considered. States and inputs are subject to hard, mixed, polytopic constraints. It is described how di ...

IEEE2009

Input-to-state stabilization of feasible model predictive controllers for linear systems

Colin Neil Jones, Melanie Nicole Zeilinger

Research on sub-optimal Model Predictive Control (MPC) has led to a variety of optimization methods based on explicit or online approaches, or combinations thereof. Its foremost aim is to guarantee essential controller properties, i.e. recursive feasibilit ...

2011

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Colin Neil Jones, Yuning Jiang, Yingzhao Lian

This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication structure corresponding to a hypergraph, by which complex relationships between ...

IEEE2023

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

Colin Neil Jones, Georgios Stathopoulos

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

Optimization of an Airborne Wind Energy System using Constrained Gaussian Processes with Transient Measurements

Colin Neil Jones, Ioannis Lymperopoulos, Sanket Sanjay Diwale

Airborne wind energy systems are built to exploit the stronger and more consistent wind available at high altitudes that conventional wind turbines cannot reach. This however requires a reliable controller design that can keep the airborne system flying fo ...

2015

Enhancing the dispatchability of distribution networks through utility-scale batteries and flexible demand

Mario Paolone, Colin Neil Jones, Fabrizio Sossan, Emil Namor, Tomasz Tadeusz Gorecki, Luca Fabietti

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan, which is computed the day before the ...

2018

A commissioning-oriented approach to data-driven modeling of buildings with heat pumps for predictive demand response

Colin Neil Jones, Manuel Pascal Koch

As the share of electricity generation from non-dispatchable sources like wind and photovoltaics grows, so does the need for demand response to stabilize the grid. Since the electricity consumption of heat pumps in buildings is both substantial and flexibl ...

Elsevier BV2025

Efficient Recursive Data-enabled Predictive Control

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

In the field of model predictive control, Dataenabled Predictive Control (DeePC) offers direct predictive control, bypassing traditional modeling. However, challenges emerge with increased computational demand due to recursive data updates. This paper intr ...

IEEE2024

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Deterministic error bounds for kernel-based learning techniques under bounded noise

Colin Neil Jones, Emilio Maddalena, Paul Scharnhorst

We consider the problem of reconstructing a function from a finite set of noise-corrupted samples. Two kernel algorithms are analyzed, namely kernel ridge regression and epsilon-support vector regression. By assuming the ground-truth function belongs to th ...

2021

Optimization of an Airborne Wind Energy System Using Constrained Gaussian Processes

Colin Neil Jones, Ioannis Lymperopoulos, Sanket Sanjay Diwale

Wind resources tend to be significantly stronger and more consistent with increasing altitude. This effect creates a potential for power generation that can be reaped by an Airborne Wind Energy system positioned at elevations exceeding the height of conven ...

2014

Real-time MPC - Stability through robust MPC design

Colin Neil Jones, Melanie Nicole Zeilinger

Recent results have suggested that online Model Predictive Control (MPC) can be computed quickly enough to control fast sampled systems. High-speed applications impose a hard real-time constraint on the solution of the MPC problem, which generally prevents ...

IEEE2009

Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies

Colin Neil Jones, Loris Di Natale

Deep Reinforcement Learning (DRL) recently emerged as a possibility to control complex systems without the need to model them. However, since weeks long experiments are needed to assess the performance of a building controller, people still have to rely on ...

2021

Economic Advantages of Office Buildings Providing Ancillary Services with Intraday Participation

Colin Neil Jones, Ioannis Lymperopoulos, Faran Ahmed Qureshi, Ali Ahmadi Khatir

Controlling the consumption profile of office buildings can be used to provide balancing services to the power grid at a financial benefit without violating its thermal comfort constraints. The economic advantage of such a service is a reduction in the tot ...

2018

Reference tracking stochastic model predictive control over unreliable channels and bounded control actions

Colin Neil Jones

A stochastic model predictive control framework over unreliable Bernoulli communication channels, in the presence of unbounded process noise and under bounded control inputs, is presented for tracking a reference signal. The data losses in the control chan ...

2021

Brunovsky Riccati Recursion for Linear Model Predictive Control

Colin Neil Jones, Shaohui Yang

In almost all algorithms for Model Predictive Control (MPC), the most time-consuming step is to solve some form of Linear Quadratic (LQ) Optimal Control Problem (OCP) repeatedly. The commonly recognized best option for this is a Riccati recursion based sol ...

IEEE2025

A Resource-Aware Approach to Self-Triggered Model Predictive Control

Colin Neil Jones

In this paper, we consider a self-triggered formulation of model predictive control. In this variant, the controller decides at the current sampling instant itself when the next sample should be taken and the optimization problem be solved anew. We incorpo ...

ELSEVIER2020

Quantization Design for Distributed Optimization

Colin Neil Jones, Melanie Nicole Zeilinger, Ye Pu

We consider the problem of solving a distributed optimization problem using a distributed computing platform, where the communication in the network is limited: each node can only communicate with its neighbors and the channel has a limited data-rate. A co ...

2017

A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand

Colin Neil Jones

This paper describes an employee scheduling system for retail outlets; it is a constraint-based system that exploits forecasts and stochastic techniques to generate schedules meeting the demand for sales personnel. Uncertain scenarios due to fluctuating de ...

Elsevier2015