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Colin Neil Jones

Related publications (224)

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Robust Resource-Aware Self-Triggered Model Predictive Control

Colin Neil Jones, Yuning Jiang, Yingzhao Lian

The wide adoption of wireless devices in the Internet of Things requires controllers that are able to operate with limited resources, such as battery life. Operating these devices robustly in an uncertain environment, while managing available resources, in ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Colin Neil Jones, Yuning Jiang, Xinliang Dai

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses signif ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

2022

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In this paper, we present the development and deployment of an embedded optimal control strategy for autonomous driving applications on a Ford Focus road vehicle. Non-linear model predictive control (NMPC) is designed and deployed on a system with hard rea ...

2021

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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

Optimal Thrust Vector Control of an Electric Small-Scale Rocket Prototype

Colin Neil Jones, Roland Schwan, Petr Listov

Recent advances in Model Predictive Control (MPC) algorithms and methodologies, combined with the surge of computational power of available embedded platforms, allows the use of real-time optimization-based control of fast mechatronic systems. This paper p ...

2021

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Model-based methods in autonomous driving and advanced driving assistance gain importance in research and development due to their potential to contribute to higher road safety. Parameters of vehicle models, however, are hard to identify precisely or they ...

2021

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

Colin Neil Jones, Bratislav Svetozarevic, 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

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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

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