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Colin Neil Jones

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Related publications (246)

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

Colin Neil Jones, Andrea Alessandretti, Ye Pu, 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

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Colin Neil Jones, Emilio Maddalena, Paul Scharnhorst, Yuning Jiang

We propose Kernel Predictive Control (KPC), a learning-based predictive control strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the unknown system dynamics are used to learn several models through the formalism of non-pa ...

2021

Robust Learning Model Predictive Control for Periodically Correlated Building Control

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

Accounting for more than 40% of global energy consumption, residential and commercial buildings will be key players in any future green energy systems. To fully exploit their potential while ensuring occupant comfort, a robust control scheme is required to ...

2021

Nonlinear Data-Enabled Prediction and Control

Colin Neil Jones, Yingzhao Lian

Behavioral theory, which characterizes linear dynamics with measured trajectories, has found successful applications in controller design and signal processing. However, the extension of behavioral theory to general nonlinear system remains an open questio ...

PMLR2021

Resource-Aware Stochastic Self-Triggered Model Predictive Control

Colin Neil Jones, Yingzhao Lian, Yuning Jiang

This letter considers the control of uncertain systems operated under limited resource factors, such as battery life or hardware longevity. We consider here resource-aware self-triggered control techniques that schedule system operation non-uniformly in ti ...

2021

Towards global optimal control via Koopman lifts

Colin Neil Jones

This paper introduces a framework for solving time-autonomous nonlinear infinite horizon optimal control problems, under the assumption that all minimizers satisfy Pontryagin's necessary optimality conditions. In detail, we use methods from the field of sy ...

2021

Guest Editorial Model Predictive Control in Energy Conversion Systems

Colin Neil Jones

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

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

From System Level Synthesis to Robust Closed-loop Data-Enabled Predictive Control

Colin Neil Jones, Yingzhao Lian

Willems' fundamental lemma and system level synthesis both characterize a linear dynamic system by its input/output sequences. In this work, we show that the extension of the fundamental lemma in uncertain LTI systems is equivalent to the system level synt ...

IEEE2021

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

Colin Neil Jones, Loris Di Natale, Bratislav Svetozarevic

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

Evaluation of advanced control strategies of electric thermal storage systems in residential building stock

Colin Neil Jones

This paper investigates the effect of different control strategies applied to electric thermal storage systems to provide demand response services. These results indicate how policymakers or manufacturers could target the implementation of advanced control ...

2021

Embedded PWM Predictive Control of DC-DC Power Converters Via Piecewise-Affine Neural Networks

Colin Neil Jones, Emilio Maddalena

Predictive control is a flexible control methodology that can optimize performance while satisfying current and voltage constraints. Its application in the power electronics domain is however hampered by the high computational demands associated with it. I ...

2021

A Demand Response-Based Solution to Overloading in Underdeveloped Distribution Networks

Colin Neil Jones

This paper addresses the problem of overloading in power distribution networks, which stems from the transmission systems being incapable of delivering power from source to consumers during peak hours. This causes frequent power-outages (or blackouts), req ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Joint Energy Management for Distributed Energy Harvesting Systems

Colin Neil Jones, Yingzhao Lian, Yuning Jiang

Employing energy harvesting to power the Internet of Things supports their long-term, self-sustainable, and maintenance-free operation. These energy harvesting systems have an energy management subsystem to orchestrate the flow of energy and optimize their ...

Association for Computing Machinery2021

Data-driven methods for building control - A review and promising future directions

Colin Neil Jones, Yingzhao Lian, Emilio Maddalena

A review of the heating, ventilation and air-conditioning control problem for buildings is presented with particular emphasis on its distinguishing features. Next, we not only examine how data-driven algorithms have been exploited to tackle the main challe ...

2020

Ancillary Services Provision Utilizing a Network of Fast-Charging Stations for Electrical Buses

Colin Neil Jones, Faran Ahmed Qureshi, Altug Bitlislioglu

Fast-charging stations that supply energy to electrical vehicles at high power rates may incorporate energy storage to avoid high currents to the grid and reduce peak-demand costs. We demonstrate the potential for utilizing such infrastructure for the prov ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

A Demand Response Framework to Overcome Network Overloading in Power Distribution Networks

Colin Neil Jones

This paper considers the problem of network overloading in the power distribution networks of Pakistan, often resulting from the inability of the transmission system to transfer power from source to end-user during peak loads. This results in frequent powe ...

ELSEVIER2020

A nonlinear model predictive control scheme for sensor fault tolerance in observation processes

Colin Neil Jones, Andrea Alessandretti

This article addresses the problem of designing a sensor fault-tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider ...

WILEY2020

On Gaussian Process Based Koopman Operators

Colin Neil Jones

Enabling analysis of non-linear systems in linear form, the Koopman operator has been shown to be a powerful tool for system identification and controller design. However, current data-driven methods cannot provide quantification of model uncertainty given ...

ELSEVIER2020

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