Publications by Colin Neil Jones

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The necessary and sufficient conditions for existence of a generalized representer theorem are presented for learning Hilbert space - valued functions. Representer theorems involving explicit basis functions and Reproducing Kernels are a common occurrence ...

The application of nuclear norm regularization to system identification was recently shown to be a useful method for identifying low order linear models. In this paper, we consider nuclear norm regularization for identification of simulated moving bed proc ...

Motivated by the increasing availability and quality of miniaturized sensors, computers, and wireless communication devices arid given their enormous potential, the use of wireless sensor networks (WSN) has become widespread. Because in many applications o ...

We consider the class of piecewise affine optimal state feedback control laws applied to discrete-time piecewise affine systems, motivated by recent work on the computation of closed-form MPC controllers. The storage demand and complexity of these optimal ...

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 ...

In this article, we consider the use of barrier functions as a regularizing cost in economic model predictive control (EMPC). We focus on a specific variant, EMPC with generalized terminal constraints (G-EMPC), as it is suitable for tackling large-scale pr ...

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 ...

Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services. In this work, we leverage this flexibility ...

Closed-form Model Predictive Control (MPC) results in a polytopic subdivision of the set of feasible states, where each region is associated with an affine control law. Solving the MPC problem on-line then requires determining which region contains the cur ...

Autonomous operation of industrial plants requires a cheap and efficient way of creating dynamic process models, which can then be used to either be part of the autonomous systems or to serve as simulators for reinforcement learning. The trends of digitali ...

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 ...

We study the problem of performance optimization of closed-loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated effective for improving closed-loop performance by automatically tuning controller gains or reference ...

This paper presents a systematic computational study on the performance of distributed optimization in model predictive control (MPC). We consider networks of dynamically coupled systems, which are subject to input and state con- straints. The resulting MP ...

We consider the class of piecewise state feedback control laws applied to discrete-time systems, motivated by recent work on the computation of closed-form MPC controllers. The on-line evaluation of such a control law requires the determination of the stat ...

We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, which admits an efficient parameterization and can be evaluated at a low comp ...

This paper presents a new formulation and synthesis approach for stabilizing cooperative distributed model predictive control (MPC) for networks of linear systems, which are coupled in their dynamics. The controller is defined by a network-wide constrained ...

In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets ...

This paper presents an investigation of how ModelPredictiveControl (MPC) and weatherpredictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort. IRA deals with the simultaneous control of heating, ve ...

Heating and cooling of buildings account for around 15% of all global energy consumption. In light of the ongoing energy transition, we aim to improve the efficiency of both in a European single-family house by using photovoltaic-thermal collectors with a ...

In this paper, convergence and performance properties of a sample-data continuous time model predictive control (MPC) scheme with economic performance index are developed. In particular, we provide sufficient conditions for convergence of the close loop st ...

Colin Neil Jones

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A Generalized Representer Theorem for Hilbert Space - Valued Functions

System identification via nuclear norm regularization for simulated moving bed processes from incomplete data sets

Distributed state estimation for discrete-time linear time invariant systems: A survey

Controller complexity reduction for piecewise affine systems through safe region elimination

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

Regularized economic model predictive control with barrier functions

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

Risk-aware scheduling and dispatch of flexibility events in buildings

A logarithmic-time solution to the point location problem for closed-form linear MPC

Recurrent Neural Network based MPC for Process Industries

Real-time Nonlinear MPC Strategy with Full Vehicle Validation for Autonomous Driving

VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints

Computational Aspects of Distributed Optimization in Model Predictive Control

Efficient evaluation of piecewise control laws defined over a large number of polyhedra

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

Distributed synthesis and stability of cooperative distributed model predictive control for linear systems

Fast Explicit Nonlinear Model Predictive Control Via Multiresolution Function Approximation with Guaranteed Stability Nonlinear Control Systems

Use of model predictive control and weather forecasts for energy efficient building climate control

A multi-modal nocturnal radiative cooling and solar-assisted heating system with model predictive control

An Economic Model Predictive Control scheme with terminal penalty for continuous-time systems