I-MECH – Smart System Integration for Mechatronic Applications

Čech, Martin; Beltman, Arend-Jan; Ozols, Kaspars

doi:10.1109/etfa.2019.8869465

Cited by 20 publications

(7 citation statements)

References 30 publications

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“…This work was supported from the H2020 ECSEL JU project I-MECH under grant agreement Nr. 737453 [20] and from ERDF under project InteCom No. CZ.02.1.01/0.0/0.0/17 048/0007267.…”

Section: Acknowledgmentmentioning

confidence: 99%

Iterative learning control in high-performance motion systems: from theory to implementation

Goubej

Meeusen

Mooren

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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Iterative learning control (ILC) enables a perfect compensation for systems that perform the same task over and over again. The aim of this paper is to demonstrate practical applicability of two various state-of-the-art ILC algorithms to point-to-point positioning systems. A simple Frequency domain ILC approach is exploited focusing on systems with exactly repeating motion tasks. Furthermore, flexible ILC is employed to enable learning also for non-repeating tasks. Particular steps providing a seamless transfer from theory and algorithms to practical implementation in a real-time environment by means of industrial-grade SW and HW are given. They may serve as a practical example of a workflow suitable for a wide range of motion control applications. Potential benefits of the learningtype control in comparison with conventional feedback and feedforward control are discussed as well.

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“…This work was supported from the H2020 ECSEL JU project I-MECH under grant agreement Nr. 737453 [20] and from ERDF under project InteCom No. CZ.02.1.01/0.0/0.0/17 048/0007267.…”

Section: Acknowledgmentmentioning

confidence: 99%

Iterative learning control in high-performance motion systems: from theory to implementation

Goubej

Meeusen

Mooren

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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“…They are key drivers of modern the cyber-physical world. As mentioned in [7], those technology areas were developed often independently in the past, hence not respecting generic principles specified by control community [8][9][10] and applicable across domains. In particular, numerous feedback control loops, vertically distributed through several layers, imply strict conditions for all elements of the ecosystem.…”

Section: Introductionmentioning

confidence: 99%

“…Smart mechatronic systems face rising constraints on speed, precision, adaptability, size, self-diagnostic and interoperability while simultaneously needing to accommodate ever more demanding smart cognitive features. Compared to [7], a list of specific challenges can be updated as:…”

Section: Introductionmentioning

confidence: 99%

Pushing Mechatronic Applications to the Limits via Smart Motion Control

2021

Self Cite

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Modern machines strive to run at limit performance and dependability while their operational area and size are getting restricted. To achieve those objectives, often swift integration of custom-made subsystems is required, either actuators, sensors, electronic, or SW modules. Such a diverse suite of elements needs specific approaches and tools for fast optimization and adjustment following model-based system engineering (MBSE) and digital twinning principles. The large-scale I-MECH project was an industry-driven initiative striving to give a scientific response to those demands. The intermediate results were summarized in the authors’ previous work. The purpose of this paper is to report on final project results, namely specific performance achievements and figures based on measurable KPIs. After a brief description of key technologies, special focus is given to industrial printing technology based on a generic substrate carrier. However, it is shown that similar and consistent methodology can be applicable in many other industrial domains, such as semiconductors, healthcare robotics, machining, packaging, etc. Thus, the main merit of this survey is a holistic approach to motion control design.

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“…Real-time wireless sensors is one of the building blocks of the recent large-scale I-MECH project [3,4], which is fully industry driven initiative trying to enable fast integration of diverse set of components (either electronic systems, software modules, sensors or actuators) for demanding mechatronic applications respecting model-based system engineering principles. In this regard, the modeling library for wireless data acquisition was developed within the aforementioned building block, which deals with robust wireless network providing reliable, synchronized and secure data delivery from sensors to the master node (or central computing unit) in an energy efficient manner.…”

Section: Introductionmentioning

confidence: 99%

Bluetooth Low Energy Wireless Sensor Network Library in MATLAB Simulink

Ozols

2020

JSAN

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The paper describes the elements of the developed MATLAB Simulink library for building the models of Bluetooth Low Energy (BLE) wireless sensor networks to simulate the communication between BLE devices in the presence of interference and channel noise. Various parameters can be configured for the devices including their 2D positions to take into account the distances between them for calculating the attenuation coefficients of the transmitted signals. Two simulation examples are provided, one of which demonstrates the data exchange between one master device and one slave at high data packet transmission rate (2 kHz), while the other example shows the data exchange between one master and multiple slaves simultaneously, in which case the data packet transmission rate can be no larger than 133 Hz.

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I-MECH – Smart System Integration for Mechatronic Applications

Cited by 20 publications

References 30 publications

Iterative learning control in high-performance motion systems: from theory to implementation

Iterative learning control in high-performance motion systems: from theory to implementation

Pushing Mechatronic Applications to the Limits via Smart Motion Control

Bluetooth Low Energy Wireless Sensor Network Library in MATLAB Simulink

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