Ramin Abbasi
PhD Candidate in Engineering Science at KU Leuven
Atlas Copco Airpower
Ramin Abbasi graduated from KU Leuven as a mechanical engineer with a focus on systems and control theory in 2017. His interest in mathematical optimization led him to research in the field of optimal control theory. His thesis focused on an optimal co-design of controllers (Linear Feedback and Model Predictive Controller) and trajectory for systems using nonlinear programming. He is investigating model predictive algorithms for compressor room control at Atlas Copco.
Project description
The aim of this project is the design and development of tailored model predictive algorithms for compressor room control, executable on constraint CPUs. A compressor room ecosystem consists of compressors, auxiliary devices, buffer vessels, and complex networks of pipes. Every compressor and the auxiliary device (dryers and air separators) that leave the production area are steered via a so-called local controller that adjusts the required pressure, sets alarms, monitors sensors, and controls the different actuators. In many cases, however, customers require air demand that cannot be provided by a single compressor, while air demand can vary throughout time. In both cases, multiple compressors are typically used in parallel. A group of compressors is termed a compressor room and is typically regulated by a central controller whose main purpose is to regulate the compressors in such a way so that they provide pressurized air in the most energy-efficient way and/or ensure an equal number of running hours for all involved compressors. Lately, new applications are emerging with a strong focus on high-quality pressurized airflows (marginal oil and particle contamination, extremely low humidity, etc.). However, current control algorithms do not have the flexibility to support these new applications. Providing control algorithms that have the flexibility to deal with a wide range of requirements (e.g., flow, pressure, air quality) puts serious constraints on the type of control technologies and requires new control algorithms and control concepts. A significantly improved control algorithm will open new opportunities, and it is expected to provide solutions with a further reduction of the energy consumption in the compressor room. MPC is believed to offer a good answer to the latter challenges.
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}
}