## Wim van Roy

PhD Candidate

**Atlas Copco Airpower**

Wim Van Roy graduated in mechatronic and robotic engineering from KU Leuven in July 2017. His interest in optimal control theory led him to the embedded controller team of Atlas Copco. As a cyber-physical systems engineer, he maintains and designs control algorithms for compressed air systems. In 2019, he started researching the use of model predictive control for compressed air systems.

## Project description

The aim of the project is to design and develop a control framework to improve the overall efficiency of compressed air systems. These compressed air systems consist of compressors, air utility devices, piping, and buffer vessels. The goal of this system is to provide compressed air to several consumers. Each of these consumers may have specific requirements on this provided flow such as minimum pressure, temperature, or humidity. The compressors in this system each have their own so-called local controller that controls the flow or pressure, monitors sensors and controls the actuators of the compressors. However, most systems consist of multiple compressors and air utility devices requiring collaboration to achieve the control goals of these systems and thus typically require centralized controllers handling the overall system control. The centralized controllers optimize global energy efficiency and ensure equal running hours as well as other system requirements. In addition, this central controller allows the handling of new emerging applications with a stronger focus on high-quality airflows (such as extremely low humidity, marginal oil, or particle contamination). The broad scope of applications as well as the large variety of system topologies requires a flexible algorithm. Current control algorithms are not capable of supporting the complete range of applications nor achieve the minimum energy consumption for these systems. They are often tailored to specific applications with a fixed topology. Providing a unified framework handling a wide variety of applications will open new opportunities and allow for a cost-effective reduction of energy consumption for compressed air systems. This research is performed in close collaboration with Ramin Abbasi.

## Publications

Roy, Wim Van; Nurkanovic, Armin; Abbasi-Esfeden, Ramin; Frey, Jonathan; Pozharskiy, Anton; Swevers, Jan; Diehl, Moritz

Continuous Optimization for Control of Finite-State Machines with Cascaded Hysteresis Via Time-Freezing Proceedings Article Forthcoming

In: 2023 Conference on Decision and Control (CDC), Forthcoming.

@inproceedings{VanRoy2023CDC,

title = {Continuous Optimization for Control of Finite-State Machines with Cascaded Hysteresis Via Time-Freezing},

author = {Wim Van Roy and Armin Nurkanovic and Ramin Abbasi-Esfeden and Jonathan Frey and Anton Pozharskiy and Jan Swevers and Moritz Diehl},

year = {2023},

date = {2023-12-01},

booktitle = {2023 Conference on Decision and Control (CDC)},

abstract = {Control problems with Finite-State Machines (FSM) are often solved using integer variables, leading to a mixed-integer optimal control problem (MIOCP). This paper proposes analternative method to describe a subclass of FSMs using complementarity constraints and time-freezing. The FSM from this subclass is built up by a sequence of states where a transition between the states is triggered by a single switching function. This can be looked at as a cascade of hysteresis loops where a memory effect is used to maintain the active state of the state machine. Based on the reformulation for hybrid systems with a hysteresis loop, a method is developed to reformulate this subclass in a similar fashion. The approach transforms the original problem into a Piecewise Smooth System (PSS), which can be discretized using the recently developed Finite Elements with Switch Detection, allowing for high-accuracy solutions. The reformation is compared to a mixed-integer formulation from the literature on a time-optimal control problem. This work is a first step towards the general reformulation of FSMs into nonsmooth systems without integer states.},

keywords = {},

pubstate = {forthcoming},

tppubtype = {inproceedings}

}

Roy, Wim Van; Abbasi-Esfeden, Ramin; Swevers, Jan

A Dynamic Programming-based Heuristic Approach for Unit Commitment Problems Proceedings Article

In: 2023 European Control Conference (ECC), pp. 1-8, IEEE, Bucharest, Romania, 2023, ISBN: 978-3-907144-08-4.

@inproceedings{vanRoy2023ADP,

title = {A Dynamic Programming-based Heuristic Approach for Unit Commitment Problems},

author = {Wim Van Roy and Ramin Abbasi-Esfeden and Jan Swevers},

url = {https://ieeexplore.ieee.org/document/10178216},

doi = {https://doi.org/10.23919/ECC57647.2023.10178216},

isbn = {978-3-907144-08-4},

year = {2023},

date = {2023-07-17},

urldate = {2023-07-17},

booktitle = {2023 European Control Conference (ECC)},

pages = {1-8},

publisher = {IEEE},

address = {Bucharest, Romania},

abstract = {Unit Commitment (UC) problems are an essential set of problems in the power industry with applications in energy grid or heating systems management and control. The engineering goal is to balance the demand with the production of a network of production units, called generators, by providing a schedule and operating points for each generator cost-effectively while considering constraints. The constraints are caused by the dynamics of the system, the limits on the reserves, and possible robustness requirements. Due to the appearance of the on/off states from the generators, the resulting problems are NP-hard to solve. Thus, existing techniques to achieve a cost-efficient solution are computationally expensive. This paper proposes a dynamic programming-based heuristic to solve a UC problem. The heuristic focuses on finding a feasible and cost-effective solution for systems with a limited number of generators where a long time horizon is important. This method is compared to a Mixed Integer Linear Program (MILP) implementation for a micro-grid where it achieves a computation time that is an order of magnitude smaller than MILP programs for problems with a limited number of generators but a long time horizon.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Abbasi-Esfeden, Ramin; Roy, Wim Van; Swevers, Jan

Iterative Switching Time Optimization for Mixed-integer Optimal Control Problems Proceedings Article

In: 2023 European Control Conference (ECC), pp. 1-6, IEEE, Bucharest, Romania, 2023, ISBN: 978-3-907144-08-4.

@inproceedings{AbbasiEsfeden2023STO,

title = {Iterative Switching Time Optimization for Mixed-integer Optimal Control Problems},

author = {Ramin Abbasi-Esfeden and Wim Van Roy and Jan Swevers},

url = {https://ieeexplore.ieee.org/document/10178419},

doi = {https://doi.org/10.23919/ECC57647.2023.10178419},

isbn = {978-3-907144-08-4},

year = {2023},

date = {2023-07-17},

urldate = {2023-07-17},

booktitle = {2023 European Control Conference (ECC)},

pages = {1-6},

publisher = {IEEE},

address = {Bucharest, Romania},

abstract = {This paper proposes an iterative method to solve Mixed-Integer Optimal Control Problems arising from systems with switched dynamics. The so-called relaxed problem plays a central role within this context. Through a numerical example, it is shown why relying on the relaxed problem can lead the solution astray. As an alternative, an iterative Switching Time optimization method is proposed. The method consists of two components that iteratively interact: a Switching Time optimization (STO) problem and a sequence optimization. Each component is explained in detail, and the numerical example is resolved, the results of which shows the efficiency of the proposed algorithm. Finally, the advantages and disadvantages of the method are discussed and future lines of research are sketched.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Roy, Wim Van; Abbasi-Esfeden, Ramin; Swevers, Jan

Online Unit Commitment Problem Solving using Extended Dynamic Programming Presentation

22.03.2023.

@misc{vanRoy2023EDP,

title = {Online Unit Commitment Problem Solving using Extended Dynamic Programming},

author = {Wim Van Roy and Ramin Abbasi-Esfeden and Jan Swevers},

year = {2023},

date = {2023-03-22},

urldate = {2023-03-22},

keywords = {},

pubstate = {published},

tppubtype = {presentation}

}