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Periodica polytechnica electrical engineering and computer science 2024年第2期68卷 213-221页

作者： Finta, Barnabás Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics University Műegyetem rkp. 3. BudapestH-1111 Hungary

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Acceleration

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LoRaWAN Sensors Integration for Manufacturing Applications via Edge Device Model with OPC UA 28

LoRaWAN Sensors Integration for Manufacturing Applications v...

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28th International Conference on Applied Electronics, AE 2023

作者： Peniak, Peter Holečko, Peter Bubeniková, Emilia Kanáliková, Alžbeta University of Žilina Žilina Faculty of Electrical Engineering Engineering and Information Technology Department of Control and Information Systems Slovakia University of Žilina Faculty of Electrical Engineering and Information Technology Department of Control and Information Systems Žilina Slovakia

ISBN: (纸本)9798350335538

The article deals with the integration of Lo(ng) Ra(nge) Wide Area Network (LoRaWAN) sensors with generic manufacturing applications and Industrial Internet of Things (IIoT) use-cases. The focus is on creating a suitable Edge device model that enables the integration of specific Long Range (LoRa) sensors together with the other generic Internet of Things (IoT/IIoT). The model is based on the Open Platform Communications Unified Architecture (OPC UA) standard, which is the most suitable integration platform for various control systems and manufacturing applications. The model was implemented in Node-RED software and subsequently validated to confirm the required integration of LoRaWAN sensors within OPC UA models. In contrast to other approaches based on integration gateway or LoRaWAN/OPC UA protocol convertors, the proposed model utilizes extended capabilities of Edge computing. It enables Edge processing and data transformation of LoRaWAN sensors data transferred by Message Queuing Telemetry Transport (MQTT) protocol from the network server, based on requirements of manufacturing applications for cloud solutions. © 2023 IEEE.

关键词： Wide area networks

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Formation control Design of Fixed-wing UAVs Based on Model Reference Adaptive control

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and Computer Science 2025年第1期69卷 43-52页

作者： Lantos, Bela Kimathi, Stephen Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Electrical and Electronic Engineering Dedan Kimathi University of Technology P.O.B. 10143 Dedan Kimathi Nyeri10100 Kenya

Formation control is currently a popular field of research due to the increasing application areas of unmanned aerial vehicles. Of concern is the stability of unmanned aerial vehicles (UAVs) formation while tracking especially under the influence of disturbances, and model parameter uncertainty. Since formation of the UAV formation while tracking, especially flying involves a mutual cooperation, consensus-based techniques are more suited such that a group of UAVs are collectively coordinated to perform some tasks. In this paper, a leader–follower formation control of homogeneous fixed wing UAVs based on model reference adaptive control with an integral error control compensation is presented. Model reference adaptive control is powerful and effective for handling uncertain and varying dynamics. This proposed distributed composite control strategy with a directed graph topology, although model-dependent can be effective to suppress disturbances affecting the vehicles, while achieving consensus-based tracking of a reference path. The numerical simulation results given show the applicability of this proposed control strategy. © 2025 Budapest University of technology and Economics. All rights reserved.

关键词： Directed graphs

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A Deep Learning Approach for Faults Recognition of Dissolved Oxygen Sensor in Wastewater Treatment Plants 28

A Deep Learning Approach for Faults Recognition of Dissolved...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Ghinea, Liliana Maria Miron, Mihaela Ratnaweera, Harsha Electrical Engineering and Electronics Faculty of Automation Computers Department of Automatic Control and Electrical Engineering Department Galaţi Romania Computers Electrical Engineering and Electronics Faculty of Automation Department of Computer Science and Information Technology Galaţi Romania Norwegian University of Life Sciences Faculty of Science and Technology Oslo Norway

ISBN: (纸本)9798350339918

Fault diagnosis in wastewater treatment plants (WWTPs) is important to protect communities and ecosystems from toxic elements discharged into water. In this sense, fault identification of sensors plays an important role as they are the key components of the water plants control, especially because environmental legislation is very strict when referring to failures or anomalies in WWTPs. This paper analyzes the performances of two Deep Learning models, a Feedforward Neural Network (FFNN) and a 1D Convolution Neural Network (1DCNN) for identifying five operating states of the dissolved oxygen (DO) sensor: normal and faulty (bias, stuck, spike and precision degradation faults). The experiments were conducted on the Benchmark Simulator Model No 2 (BSM2) developed by the IWA Task Group. The performance of the Deep Learning (DL) classifiers was evaluated via accuracy, precision, recall, and F1-score metrics. The best overall classification accuracy was obtained by FFNN, 98.32% for training and 98.30% for testing. © 2023 IEEE.

关键词： Wastewater treatment

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A Collaborative Graph-based SLAM Framework Using a Computationally Effective Measurement Algebra

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2023年第4期67卷 403-412页

作者： Péter, Gábor Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

Simultaneous localization and mapping (SLAM) is an essential task for autonomous rover navigation in an unknown environment, especially if no absolute location information is available. This paper presents a computationally lightweight framework to enable agents with limited processing power to carry out the SLAM cooperatively and without absolute onboard localization sensors in a 2D environment. The proposed solution is built on a graph-based map representation, where nodes (resp. edges) represent landmarks (resp. odometry-based relative measurements), a measurement algebra with embedded uncertainty, and a compact database format that could be stored on a server in a centralized manner. The operations required by the agents to insert a new landmark in the graph, update landmark positions and combine measurements as a loop is closed in the graph are detailed. The resulting framework was tested in a laboratory environment and on a public dataset with encouraging results;hence our method can be used for cost-effective indoor mobile agents with limited computational resources and onboard sensors to achieve a mapping while keeping track of the agent’s position. The method can also be easily generalized for a 3D scenario. © 2023 Budapest University of technology and Economics. All rights reserved.

关键词： Mobile agents

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Hybrid Optimization Algorithm for Handwritten Document Enhancement

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Computers, Materials & Continua 2024年第3期78卷 3763-3786页

作者： Shu-Chuan Chu Xiaomeng Yang Li Zhang Václav Snášel Jeng-Shyang Pan College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China Faculty of Electrical Engineering and Computer Science VŠB-TU OstravaOstrava70080Czech Republic Department of Information Management Chaoyang University of TechnologyTaichung41349Taiwan

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

关键词： Metaheuristic algorithm gannet optimization algorithm hybrid algorithm handwritten document enhancement

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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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2023 International Conference on electrical, Computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Kaučić, Luka Kovačević, Ivana Aleksi, Ivan Keser, Tomislav Zidar, Josip Rimac-Drlje, Snježana Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Computer Engineering and Automation Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Communications Osijek Croatia

ISBN: (纸本)9798350322972

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs. © 2023 IEEE.

关键词： Fermentation

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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Pointer Meter Reading under Noise Based on Virtual Data Generation

Pointer Meter Reading under Noise Based on Virtual Data Gene...

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2024 China automation Congress, CAC 2024

作者： Zhu, Jinyang Xu, Zhezhuang Lin, Ye College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Using machine vision for meter reading significantly enhances the efficiency of industrial monitoring. However, meters in outdoor environment are often subject to the noise such as rain and fog, which affect the accuracy of meter readings. Additionally, the meter images and labels under noise are hard to obtain. To address these challenges, We propose a method for pointer meter reading under noise based on virtual data generation. Firstly, We utilize Unity to construct an industrial meter scene, which generates the images of meter under noise and theri labels. Secondly, we develop a U-Net network with an ASPP module, which expands the receptive field of network and enhances the ability of segmentation network to capture global semantic information under noise. Finally, the angular method is used to calculate the meter readings. Experimental results show that this method can effectively read meters under noise in outdoor environments. © 2024 IEEE.

关键词： Virtual addresses

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Semi-supervised learning with GAN for Semantic Segmentation of Wood Defect image

Semi-supervised learning with GAN for Semantic Segmentation ...

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2024 China automation Congress, CAC 2024

作者： Zheng, Kunxin Zheng, Song Xu, Zhezhuang Lin, Ye Zhu, Yuhang College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Automatic defect detection on wood surface is essential for ensuring product quality. Semantic segmentation methods have shown outstanding performance in wood defect detection. However, it is costly to acquire correct pixel-level labels of wood surface defects due to the complicated characteristics. To mitigate the cost of acquiring high-quality datasets, this study proposes a semi-supervised defect detection approach based on generative adversarial networks, which contains a generator and a discriminator. The generator is utilized to generate pixel-level segmentation results of wood defect images. To improve the segmentation performance, the discriminator learns against the generator by judging the goodness of the prediction results and generates supervised signals for the prediction results of unlabeled images. With this learning model, the proposed method can enhance segmentation performance using unlabeled images and alleviate the burden of data annotation. We validate the effectiveness of the proposed approach on a collected dataset of wood defects. Experimental results demonstrate the remarkable performance of our method even when utilizing only a small amount of annotated data. © 2024 IEEE.

关键词： Generative adversarial networks

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