Ústav automatizace a měřicí techniky
Browse
Recent Submissions
- ItemParallel Computing Utilization in Nonlinear Model Predictive Control of Permanent Magnet Synchronous Motor(IEEE, 2024-09-09) Kozubík, Michal; Veselý, Libor; Aufderheide, Eyke; Václavek, PavelPermanent Magnet Synchronous Motor (PMSM) drives are widely used for motion control industrial applications and electrical vehicle powertrains, where they provide a good torque-to-weight ratio and a high dynamical performance. With the increasing usage of these machines, the demands on exploiting their abilities are also growing. Usual control techniques, such as field-oriented control (FOC), need some workaround to achieve the requested behavior, e.g., field-weakening, while keeping the constraints on the stator currents. Similarly, when applying the linear model predictive control, the linearization of the torque function and defined constraints lead to a loss of essential information and sub-optimal performance. That is the reason why the application of nonlinear theory is necessary. Nonlinear Model Predictive Control (NMPC) is a promising alternative to linear control methods. However, this approach has a major drawback in its computational demands. This paper presents a novel approach to the implementation of PMSMs' NMPC. The proposed controller utilizes the native parallelism of population-based optimization methods and the supreme performance of field-programmable gate arrays to solve the nonlinear optimization problem in the time necessary for proper motor control. The paper presents the verification of the algorithm's behavior both in simulation and laboratory experiments. The proposed controller's behavior is compared to the standard control technique of FOC and linear MPC. The achieved results prove the superior quality of control performed by NMPC in comparison with FOC and LMPC. The controller was able to follow the Maximal Torque Per Ampere strategy without any supplementary algorithm, altogether with constraint handling.
- ItemVarroa destructor detection on honey bees using hyperspectral imagery(Elsevier, 2024-09-01) Duma, Zina-Sabrina; Zemčík, Tomáš; Bilík, Šimon; Sihvonen, Tuomas; Honec, Peter; Reinikainen, Satu-Pia; Horák, KarelHyperspectral (HS) imagery in agriculture is becoming increasingly common. These images have the advantage of higher spectral resolution. Advanced spectral processing techniques are required to unlock the information potential in these HS images. The present paper introduces a method rooted in multivariate statistics designed to detect parasitic Varroa destructor mites on the body of western honey bee Apis mellifera, enabling easier and continuous monitoring of the bee hives. The present paper is the first to utilize hyperspectral imagery for the task, previous studies existing only for multispectral imagery. The methodology explores unsupervised (K-means++) and recently developed supervised (Kernel Flows-Partial Least-Squares, KF-PLS) methods for parasitic identification. Additionally, in light of the emergence of custom-band multispectral cameras, the present research outlines a strategy for identifying the specific wavelengths necessary for effective bee-mite separation, suitable for implementation in a custom-band camera. Illustrated with a real-case dataset, our findings demonstrate that as few as four spectral bands are sufficient for accurate parasite identification.
- ItemIndustry 4.0 demonstrator: COMBED(ELSEVIER, 2024-08-14) Braun, Vlastimil; Zezulka, František; Marcoň, Petr; Jirsa, Jan; Fiedler, Petr; Kaczmarczyk, Václav; Arm, Jakub; Bradáč, Zdeněk; Dohnal, PřemyslThe paper discusses the manufacturing procedures and modes that will be employed in smart factories in the course of the next stage of technology development within the 4th Industrial Revolution. The manufacturing modes integrate the principles of Industry 4.0 (I4.0), presented through specifications by German, French, and Italian standardization committees. At present, the individual aspects of the entire system, which comprises technological means, functions, services, management structures, and requirements on manufacturing components and products in factories of the future, are being standardized. In our research, this 14.0 -based mode of production is demonstrated on a virtual testbed. Compared to the costly physical testbeds, whose application is limited physically as well as in terms of funding and time, the virtual approach allows showing the 14.0 manufacturing principles effectively and cheaply. For this purpose, we employ two versions of the COMBED, a virtual testbed; in this context, the principles are exposed as facilitating consistent production management decentralization via standardized Asset Administration Shell (AAS) digital twins in both the individual manufacturing components and the actual product. The paper is complemented with viderecordings that expose the model functions of a smart factory producing simple plastic models of various cars by using robots, automated machines and stores, 3D printers, and other manufacturing components equipped with standardized digital twins (AASs). Copyright (c) 2024 The Authors.
- ItemUse of Multi-Agent System for Industrial Production Control(Elsevier, 2024-08-14) Jirsa, Jan; Zezulka, František; Marcoň, Petr; Pečinka, Tomáš; Nováček, Ladislav; Kaczmarczyk, Václav; Arm, JakubThis paper describes specific implementation of Asset Administration Shell technology used for an industrial distributed control system. The base of this control system is a multiagent system of digital twins which was created by AAS. This multiagent system was developed for a specific platform CP Factory (mainly based on Simatic PLC) but the implementation is y portable to each common platform. Digital twin of several types of components of typical industrial production process are described in this paper with the implementation of active and passive administration shell. The main focus is on describing the way of integrating digital twins into the production system and the necessary SW tools. Industry 4.0 language was used as a common communication protocol as well as OPC UA and MQTT.
- ItemA Method of Tactile Resistive Sensor Array Calibration(Elsevier, 2024-08-14) Husák, Michal; Mihálik, Ondrej; Dvorský, Petr; Bradáč, ZdeněkResistive sensor arrays (RSA) comprising of pressure-sensitive elements find broad use in pressure-sensing applications. However, sensor manufacturing inevitably yields a number of non-ideal properties. The gain, offset or non-linearities of an RSA’s elements may vary between individual sensors (taxels). Hence a simple calibration procedure to suppress these effects is desirable. The paper presents a method of and apparatus for the calibration of a pressure-sensing RSA. A forward mathematical model for each sensor is obtained during the calibration phase. In subsequent online measurement, the inverse model is utilised to compensated for the non-uniformity in sensor gain and offset. This approach leads to an appreciable improvement in picture quality, which can be mathematically quantified using classification accuracy in our tactile anti-decubitus platform for human monitoring. Namely, in a four-class classification experiment involving a support vector machine, the classification error decreased from 11 % before calibration to 3.5 % after calibration. Owing to the calibration procedure, a classifier trained using a calibrated RSA can be deployed to another calibrated RSA, without further data collection.