Stijn Derammelaere associate professor

Research Stijn Derammelaere

Research team

Expertise

As the control algorithms directly drive the actuators, the controllers have a significant influence on the productivity, energy usage, quality and robustness requirements. To optimize the performance of the control towards these requirements, the research of professor Derammelaere considers four essential topics. First of all, his attention goes to the control algorithm and more important control architecture. Secondly, research on the optimal selection, optimal placement of sensors and implementation of feedback estimation guarantees cost-efficient control. Furthermore, next to control optimizations, trajectory optimization improves the energy-usage and output of the machine. Finally, all these issues; control architecture, feedback optimization and estimation and path planning deliver the best results if a reliable dynamic system model is available.

Online Global Motion Profile Optimizer. 01/11/2024 - 31/10/2026

Abstract

To address environmental concerns, researchers focus on reducing the energy use of industrial machinery. Position-controlled systems allow for energy savings by optimizing the position function between fixed user-defined start and endpoints, requiring only adjusted drive settings for easy and cost-effective implementation. State-of-the-art optimizers rely on complex, machine-specific models, deterring machine builders. Furthermore, mismatches between model and reality, and changes in machine behavior over time can render optimized motion profiles suboptimal in practice. This project proposes a novel solution by optimizing the motion profile online during machine operation. Moreover, a key issue is that existing algorithms often achieve only local optimum motion profiles, potentially missing up to 11.3% of energy savings compared to the global optimum. This project proposes two steps to achieve global optimum motion profiles. First, the use of a global optimization algorithm. Secondly, the motion profile's mathematical formulation, typically constrained to specific bases (e.g., polynomial, splines), can limit revealing the global optimum. This project will employ Gaussian Processes to describe motion profiles, allowing unconstrained optimization potential by not limiting the profile to a specific form. Only an online motion profile without pre-defined profile bases can result in a machine operation with an absolute minimal energy need.

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  • Research Project

Drive Line Concept Optimization (AnCoOpt). 01/10/2023 - 30/09/2025

Abstract

he AnCoOpt project aims to develop tools and methodologies for the conversion of customer inquiries into optimal machine concepts for electric positioning applications. This is achieved by minimizing component costs, energy consumption, and material usage, while maximizing performance through the utilization of commonly used CAD tools. The project specifically targets Flemish machine manufacturers, engineering consultants, and providers of drive components and CAD software.

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Sparse interpolation for high-dimensional mechatronic co-design. 01/01/2023 - 31/12/2026

Abstract

The design and engineering of electrically driven machine mechanisms increasingly rely on optimisation. This allows the minimisation of objectives such as the initial component cost or electrical energy required to drive these machines, all without compromising the performance. Heuristic optimisers, popular in mechatronics, often result in local optima and so leave a significant untapped optimisation potential. Different domains such as trajectory, geometry, and controller should be optimised simultaneously in a co-design approach to find the global minimum. Therefore, an explicit model of the design variable's impact on the objective is required. However, the data collection necessary for such a high-dimensional model, simultaneously considering all the design parameters, results in an explosion of the needed number of motion simulations. So, the co-design objective is only attainable if the model can be built from a minimal number of simulations. Through recent developments in multi-dimensional data fitting techniques, a practically feasible method for co-design in a high-dimensional setting may now become available for the first time.

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  • Research Project

Capacitive Wireless Power Transfer for MIMO Configurations. 01/10/2022 - 30/09/2026

Abstract

Capacitive wireless power transfer (CPT) applies the electric field to transfer energy from a transmitter to a receiver without the need of physical connections. However, depending on the distance between transmitter and receiver, and their relative alignment, the system performance varies. A CPT system that automatically positions itself in the optimal working point, regardless the value of the unpredictable coupling, is therefore necessary. This is in particular challenging for a setup with multiple transmitters and multiple receivers, i.e., a Multiple Input – Multiple Output (MIMO) configuration. The objective of this project is to determine the necessary fundamental relationships to enable and implement algorithms to keep the operating conditions of a MIMO CPT system optimized.

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On-line optimization of ISOL@MYRRHA performance through an intelligent and automated control system. 01/01/2022 - 31/12/2025

Abstract

ISOL@MYRRHA is the Isotope Separation On Line facility to be constructed in the first phase of the MYRRHA project. It will be capable to produce a large variety of radioactive isotopes for applications in the field of nuclear physics, condensed-matter physics, biology, nuclear medicine and others. The quality (purity) and quantity (intensity) of the supplied RIB depends heavily on the proper tuning of the underlying process steps and their mutual interaction. From feedback of running ISOL facilities (ISOLDE/TRIUMF) it is known that the operation of an ISOL system needs constant intervention of an experienced operator/user. His job is to adjust the operational parameters of the system at a regular basis to compensate for effects likes ageing of the target and ion source, foiling of the extraction electrode, aligment issues due to temperature effects, etc ... . ISOL@MYRRHA aims at providing long uninterrupted beam times whichout compromising the quality and quantity of the beams to the users. An online optimization (retuning target, ion source and RIB transport parameters, ...) would unsure the continous delivery of the RIB to the users at optimal parameters and without interuptions. In this project, a control strategy will be developed to provide initial optimal selection of the control parameters as well as provide online tuning to keep the system continuously in the optimal operational regime.

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Nexor - Cyber-Physical Systems for the Industry 4.0 era 01/01/2021 - 31/12/2026

Abstract

The fourth industrial revolution (Industry 4.0 as it is commonly referred to) is driven by extreme digitalization, enabled by tremendous computing capacity, smart collaborating machines and wireless computer networks. In the last six years, Nexor — a multi-disciplinary research consortium blending expertise from four Antwerp research labs — has built up a solid track record therein. We are currently strengthening the consortium in order to establish our position in the European eco-system. This project proposal specifies our 2021 - 2026 roadmap, with the explicit aim to empower industrial partners to tackle their industry 4.0 challenges. We follow a demand driven approach, convincing industrial partners to pick up our innovative research ideas, either by means of joint research projects (TRL 5—7) or via technology licenses.

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  • Research Project

Dotation for the structural collaboration with Flanders Make. 01/01/2021 - 31/12/2024

Abstract

Flanders Make's mission is to strengthen the international competitiveness of the Flemish manufacturing industry on the long term through industry-driven, precompetitive, excellent research in the field of mechatronics, product development methods and advanced production technologies and by maximizing valorisation in these areas.

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eMotioniser: Development of an online tool for optimal designing of electrically driven positioning applications. 01/09/2023 - 31/08/2024

Abstract

Designing an electrically driven positioning driveline involves lots of dimensioning and selection. Selecting the correct components and designing the motion profiles, machine geometries, and controllers, … all have a major impact on the initial component cost, required electrical energy to drive the application, and machine performance …. In other words, each selection and design choice can be considered a design parameter in an optimisation that maximises performance, such as machine throughput and simultaneously allows the minimisation of cost and required electrical energy. In 2017, our research group started developing algorithms to optimise the design of electrically driven machines. In cases where we applied our algorithms, it is not uncommon to see a reduction in required electrical energy of 67%, while at the same time, the component cost could be reduced by 30%. In other cases, we could improve the accuracy by 93% or improve the speed of the machines by 43%. All cases handled by our research group clearly show the potential benefits for industrial machine builders in terms of cost minimisation and performance maximisation. However, the algorithms we developed can only create value if we expand the scope of possible industrial usersinterested in applying our techniques beyond our local contacts with whom we regularly collaborate. Each machine builder in Europe and worldwide can benefit by applying our algorithms! To enable this European and worldwide outreach, an online tool which can be conveniently used by small up to international machine builders is envisaged. Such a tool should run our algorithms in the back with a graphical user interface that only requires machine parameters known or identifiable by the envisaged machine designers. This project contains two important parts. First of all, the concerned web tool should be developed. Secondly, the best path to a self-sustaining tool will be initiated.

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Optimisation of the flexibility in a driveline through virtual engineering (OptiFlex). 01/10/2021 - 30/09/2023

Abstract

The OptiFlex project, executed by Ghent University, University of Antwerp, and KU Leuven, has developed rapid deployment methodologies and tools to quantify and simulate flexibility in drivetrains. As a result, flexibilities can be compensated by optimizing motion profiles and controller settings. This has led to notable successes, such as a speed enhancement of 52% in the cyclical motion of a loom machine and determining the impact of flexibility on the cutting accuracy of a plasma cutting table. These findings emphasize the significance of gaining knowledge about your drivetrain system and employing optimized motion controllers and motion profiles.

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Sparse interpolation potential in multidimensional optimisations. 01/10/2020 - 30/09/2024

Abstract

In engineering, simulations access the impact of design changes applied by engineers. Based on the simulation output, the engineer improves the design. Recently the engineer is replaced by an optimisation algorithm which adapts the design parameters to ensure optimal performance. Literature mentions case where applying these optimisation techniques leads to performance improvements up to 33%. However, current state-of-the-art very often relies on heuristic optimisation techniques. While they are easily applicable and suited for many applications, they cannot at all guarantee to find the global optimum. In contrast to local optima, the global optimum is the unique design which guarantees the best performance. Using optimisers which cannot guarantee the global optimum very often result in an untapped potential of up to 18%. Nevertheless, heuristic optimisers are still preferred in engineering as they do not require an exact mathematical model of the objective function. We propose to identify the mathematical model based on simulations standard in engineering practice. These simulations can deliver samples of the objective function based on specific settings for the design parameters. However, if the number of design parameters increases, providing an accurate grid of objective function samples becomes inconceivable as the number of necessary simulations explodes. Recent advances, obtained by the co-promotor, in multidimensional sparse interpolation will be a game-changer as it would reduce the number of necessary samples to an absolute minimum. By doing so, the underlying mathematical model we identify the objective function. This enables exact global optimisation. The research in this proposal will result in a generic workflow starting from commonly used simulations leading to a model via multidimensional sparse interpolation. The fact that such a model will enable global optimisation of engineering problems with multiple design parameters will be a genuinely fundamental novelty for the mechatronic state of the art.

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Towards optimal design, trajectories and control for repetitive movements. 01/11/2019 - 31/10/2023

Abstract

There is a strong desire to maximize the efficiency or speed of industrial machinery. Designers of machines, performing repetitive motions, often only define the position start- and endpoint of a movement and not the exact position function. This flexibility opens the opportunity to optimize the trajectory of the mechanism. Moreover, for the machine design itself, machine builders often rely on standard components and dimensions. The effect of the geometric design on the optimal trajectory and energy need of the system is very often neglected. The literature mentions cases where ad-hoc optimizations reduce energy usage up to 39% thanks to trajectory and geometric optimization. This project will use available CAD models and sparse interpolation to extract a closed mathematical system property description. This will enable using an interval optimization technique which can guarantee to find the one true global optimal geometric design and trajectory. The knowledge of the system properties will be used to design a robust controller to ensure the machine follows the desired trajectory. Finally, any mismatch between the virtual and real model will be detected with online tracking techniques to assure the machine operation remains optimal. The potential impact for machine builders is high as this project enables them to construct machines with a reduced total cost of ownership or allow them to perform a task as fast as possible purely based on their readily available CAD models.

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Optimal machine design by means of virtual engineering (OPTIMOTION) 01/10/2019 - 30/09/2021

Abstract

The overarching objective of this project is to develop tools and train the members of the target group in their usage. These tools should allow the straightforward optimisation of the mechanical design of machines and their drive system. Optimizing the placement of essential machine parts and optimising the selection of drive components can minimize the drive torque required for a machine. This optimisation potential can be fully exploited if the motion controller that drives the whole is properly tuned. All Flemish companies involved in mechanical engineering operate in a competitive market and are under pressure to optimise their machine design. More specifically, this project is aimed at machine builders, engineering consultants and suppliers of drive components and CAD software.

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Opticharge. 01/12/2018 - 30/11/2020

Abstract

In the Opticharge project existing technological solutions for the automation of loading and unloading operations will be analysed, as well as innovative solutions that are being developed by technology providers, research institutions and universities. In a next step, these technologies will be linked to the needs of the companies participating in the project. These needs are examined by the Flemish Institute for Logistics. The project also includes the development of a tool, presented in a matrix, in order to calculate the ROI of the different technological solutions.

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Development of a priori and online trajectory optimisation for repetitive motions. 01/10/2018 - 30/09/2022

Abstract

As global energy demand will continue to rise and man's negative impact on global warming is known to be a fact, there is a strong desire to minimise the energy usage of industrial machinery. A significant opportunity lies in optimisations which do not require any adaptations or investments in installed hardware such as trajectory optimisation. Machine builders and users often only define the time to move from one point to another and the position of start- and endpoint. The exact position as a function of the time, or position function, in between these two points is very often not an issue for machine users. This flexibility opens the opportunity to optimise the position function. The literature mentions cases where ad-hoc optimisations reduce the energy usage of machinery used for repetitive tasks up to 50% by choosing optimised trajectories over the usual standard movement profiles. However, there is no scientific consensus on a computationally efficient technique which can guarantee to find the global optimum for systems with position varying mechanical load properties. Therefore, this project will assess the use and implementation of direct calculus optimisation. Applying this pure mathematical technique based on symbolic methods of trajectory optimisation would be a genuinely fundamental novelty, especially for machines with position varying dynamics. For one thing, this would eliminate the necessity of time-consuming iterative optimisations. On the contrary, direct calculus methods would lead to closed mathematical functions for the position function. To enable the use of this direct calculus methods, closed mathematical equations, describing the position-varying mechanical load properties, will be necessary. Obtaining such functions can be done theoretically based on Lagrange formulations. However, such an approach is not feasible in practice where the complexity of the machinery hampers analytical analysis. On the other hand, machine builders increasingly rely on CAD multibody software to design their machines. The promotor has expertise in extracting data by applying specific simulations on these virtual CAD models. The sampled data, obtained in this way, can be translated to explicit formulas, based on the expertise of the co-promotor. Developing such a technique to transform the sampled data to closed mathematical equations will be a core challenge of the project and the major enabler to apply direct calculus optimisation. Furthermore, to guarantee the machine still operates at its optimum if machine behaviour changes during operation, an online tracking method is necessary. For this purpose, the knowledge of the promotor on tracking the position dependency of machine parameters online in the frequency domain is essential. The data samples obtained in this way will again be translated to a mathematical description to allow a re-optimisation of the trajectory. For this purpose, the direct calculus optimisation method will be advantageous as it defines the optimised path as a function of position varying parameters. This definition enables direct re-optimisation. Moreover, where the current state of the art focusses on offline a priori or online optimisation, facilitating online re-optimisation based on a priori offline determined information will be another fundamental novelty of this project.

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  • Research Project

High-efficiency Sensorless Control of a BLDC Motor using Sinusoidal Currents. 01/07/2018 - 31/12/2019

Abstract

A Brushless DC Machine (BLDC) is the optimal motor to use in applications where a more or less constant, controlled, high rotational speed is required. Typical examples include driving: the compressor of a cooling system including refrigerators and air-conditioning, the propellers of a drone, fans and pumps in general, …. The BLDC is responsible for the lion share energy usage of these applications. Moreover, cooling systems consume a lot of energy worldwide because of their ubiquitous presence. On the other hand, for battery fed systems such as drones there is strong desire for increased autonomy. This means there is a strong desire to reduce the energy usage of BLDC driven systems. BLDC motors are typically driven with a square wave current. On the other hand, using sine wave currents could result in an energy efficiency increase of 10%. However, typical BLDC algorithms lack feedback to drive the machine with sine waves. Using an encoder to obtain this position feedback would increase the cost and complexity of the drive system and can be impossible due to limited mounting space. Therefore, so-called sensorless algorithms which estimate feedback signals based on easily measurable voltage and current signals, are of interest. Consequently, the central research question of this STIMPRO is formulated as: Develop and implement a sensorless algorithm to provide feedback for a BLDC drive algorithm using sinusoidal current waveforms and validate its energy saving potential. As a starting point this STIMPRO will consider an estimation algorithm, developed by the promotor, for stepping motors, to use in BLDC drives. This STIMPRO will be used as a kick-start to initiate electrical motor control research at UAntwerp. This project will serve as leverage to move the activities off the promotor in motor control, who started at ZAP at UAntwerp the 1st of September 2018, previously established at UGent to UAntwerp. To do so, the STIMPRO will be used to hire a researcher who will submit an FWO SB proposal. However, if FWO funding is rejected we will not finish this project empty handed. Given the work plan defined in the STIMPRO, and the experience of the promotor the project will certainly result in publications, a test bench, added experience for the hired researcher and the exploration of possible bilateral collaboration with Flemish companies on the subject. The work done in this STIMPRO will be beneficial for the Op3Mech research group as adding research on electrical motors is a vital in the broader robotics research. Moreover, the education on drivelines at the Faculty of Applied Engineering is currently not supported by academic research. Therefore, the research activities initiated in this STIMPRO are vital to continue education on these topics.

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