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43rd Chinese control Conference, CCC 2024

作者： Song, Tian-Shu Chen, Zhen-Peng Hou, Hui-Rang Li, Hong-Yue Meng, Qing-Hao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China

ISBN: (纸本)9789887581581

Detecting ignitable liquids (ILs) at the scene of a fire is crucial for fire investigation. The electronic nose (e-nose) is crucial for detecting ILs due to its affordability and rapid response time. process limitations and changes in environmental conditions can cause variations in the reactions of multiple e-noses with the same sensor array to the same input gas. This can significantly reduce the accuracy of identifying ILs when deploying a model trained on one e-nose to other e-noses. In order to tackle the issue of cross-platform identification of ILs using e-noses, we developed a feature mute gated network (FMG-Net). This network is capable of maintaining consistency in the shared components of different e-noses at the low-level feature level while effectively muting the distinct low-level features. FMG-Net is comprised of a main network and multiple branch networks that are specific to different domains. Initially, a subsidiary domain-specific convolutional neural network (SDS-CNN) is trained to learn the network parameters on various e-nose platforms with known labels. Additionally, the backbone network generates low-level features of the e-nose responses. Furthermore, the SDS-CNN incorporates random input of low-level features and generates a mask using the gradient. This mask is then used to explicitly remove the non-overlapping parts of the low-level features. At last, the low-level features are sent back to the backbone network for further training once the non-overlapping parts have been removed. Experiments were conducted to identify four types of ILs (diesel, gasoline, ethanol, and thinner) using five self-made e-nose platforms with identical sensor arrays. The results indicated that the proposed FMG-Net consistently outperforms other domain-generalization algorithms in terms of recognition accuracy and parameter sizes. FMG-Net has the ability to detect volatile gases in ILs using an e-nose, even without the need for a dataset. © 2024 Technical Committ

关键词： Convolutional neural networks

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A Multi-Gas Detection System Based on Convolutional Neural Network 43

A Multi-Gas Detection System Based on Convolutional Neural N...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Si-Wen Li, Hong-Yue Hou, Hui-Rang Meng, Qing-Hao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China

ISBN: (纸本)9789887581581

The emission of carbon oxides (COx), nitrogen oxides (NOx), sulfur compounds, and volatile organic compounds (VOCs) from vehicles has significantly impacted the air quality, thus posing threats to the environmental resources and human health. This work presents the development of a non-dispersive infrared (NDIR) multi-gas detection system featuring three broadband light sources, a sealed gas chamber, and three multi-channel pyroelectric detectors with a response time shorter than 32 ms. The proposed system is used for constructing an odor dataset comprising five target gases, including carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), sulfur dioxide (SO2), and propane (C3 H8). We perform odor recognition experiments using the traditional machine learning methods, as well as one-dimensional convolutional neural network (1D-CNN) and depthwise separable convolutional neural network (DS-CNN). The results show that the proposed DS-CNN model achieves an accuracy of 94.75% in recognizing different odors, thus outperforming other classification algorithms. This work demonstrates that the proposed detection system exhibits rapid response and precise recognition, thus establishing it as an effective approach for analyzing the primary components of automobile exhaust. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Air quality

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A Depression Level Classification Model Based on EEG and GCN Network with Domain Generalization 43

A Depression Level Classification Model Based on EEG and GCN...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Zhongyi Xu, Chenyang Jin, Licheng Hou, Huirang Meng, Qinghao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China

ISBN: (纸本)9789887581581

Electroencephalography (EEG) contains a wealth of information, including neuron activity, allowing for a partial understanding of the brain's state. As a reliable tool, EEG, combined with deep neural networks, has been increasingly utilized to assist in the detection of depression and has achieved satisfactory results. However, there are still some limitations in the current models. Firstly, it is worth noting that many existing models are binary classification models. These models can determine whether a subject is depressed or not, but they lack the capability to differentiate the severity of depression. Besides, the variations in EEG signals among various individuals have not been thoroughly taken into account, leading to subpar performance when applying the trained model to new subjects. To address the aforementioned issues, we suggest implementing a multi-classification model that utilizes a graph convolutional neural network (GCN) to identify levels of depression. Additionally, to mitigate the problem of imbalanced samples in multi-classification tasks, we introduce a penalty coefficient for the smaller categories. At the same time, the issue of signal discrepancies among subjects was taken into account, leading to the introduction of the domain generalization module. Finally, the depression level identification task on the MODMA and PRED+CT dataset achieved an accuracy of 75.47% and 77.97% respectively, surpassing the performance of the state-of-the-art (SOTA) model. In addition, numerous ablation experiments were conducted to validate the efficacy of each module. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Convolution

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Model Predictive control Based Reference Generation for Optimal Proportional Integral Derivative control 32

Model Predictive Control Based Reference Generation for Opti...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Gashi, Fatos Abuibaid, Khalil Ruskowski, Martin Wagner, Achim KaiserslauternD-67663 Germany RPTU Kaiserslautern-Landau Machine Tools and Control Systems Department of Mechanical and Process Engineering KaiserslauternD-67663 Germany

ISBN: (纸本)9798350395440

We introduce an alternative approach towards optimal proportional integral derivative (PID) control, consisting of model predictive control (MPC) based reference generation. To this end, we have integrated the reference as part of optimization variables of the resulting problem, where a deliberate sequence of errors is induced to obtain an optimal PID control action. In addition, the desired behavior of the PID controller is achieved without the need for internal modification of the PID gains. To better highlight the ability of coping with poor PID tuning, several test cases consisting of progressively degraded PID gains are presented. Validation of the proposed strategy is displayed by comprehensive simulations using two different plants. © 2024 IEEE.

关键词： Model predictive control

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Real-time power flow analysis and management for a long-endurance solar UAV during continuous flight

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CEAS Aeronautical Journal 2023年第4期14卷 1035-1049页

作者： Ghelem, Nourddine Boudana, Djamel Bouchhida, Ouahid Laboratory of Process Control LCP Department of Engineering Control Systems and Applied Mathematics National Polytechnic School ENP of Algiers 10 St Hacen Badi El Harrach Algiers Algeria Department of Electrical Engineering LREA Laboratory University of Medea Medea Algeria

One of the primary challenges for Unmanned Aerial Vehicle (UAV) developers is to improve their endurance while in the air, as their typical flight time is limited to a few hours. One widely used technology to enhance their endurance is harnessing solar energy to power UAV and charge their batteries in flight. This article presents the development of a real-time simulation environment to enable the continuous flight of the Sky Sailor solar UAV. Through the utilization of a solar irradiance model, a solar panel model, real-time power generation is calculated. Simultaneously, the UAV’s full dynamic model, along with the autopilot and propulsion system model, is employed to determine the energy consumption at each moment. The energy management algorithm then compares the acquired energy with the power consumed, and in cases of surplus energy, it is efficiently stored in the battery for nighttime usage. Simulations show that continuous flight of the drone can be achieved during the summer season, when the daylight hours are long enough to fully charge the battery, With the ability to fly continuously during this period, the UAV can be used in various areas, such as monitoring forest fires, agricultural fields, beaches, and security monitoring for oil companies and their life bases in deserts. © 2023, Deutsches Zentrum für Luft- und Raumfahrt e.V.

关键词： Solar energy

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Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques

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Sustainable Energy Research 2024年第1期11卷 1-12页

作者： Sadeghi, Kiavash Hossein Shafikhah, Mahmood Marashian, Arash Roshandel, Emad Razminia, Abolhassan Department of Electrical Engineering Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Process Control Laboratory Faculty of Natural Sciences and Engineering Åbo Akademi University Turku Finland College of Science and Engineering Flinders University Adelaide Australia

The development of a dynamic model for a popular implemented solar power plant is a critical task for power engineers aiming to enhance the plant’s performance and reliability. In this study, we utilized the prediction error method (PEM), a robust algorithm for system identification, to capture the plant’s operational characteristics with precision. Additionally, we employed both recursive and hierarchical algorithms to identify the system parameters effectively. The results from each identification method are rigorously quantified and analyzed, allowing for a detailed comparison of their performance. This comprehensive evaluation not only highlights the strengths and weaknesses of each approach, but also provides valuable insights into their practical applications in the context of solar power systems. © The Author(s) 2024.

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Architecture of Digital Twin for Automating Waste and Recycling Material Sorting process

Architecture of Digital Twin for Automating Waste and Recycl...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Shreyas Parbat Imam Iqbal Isabell Viedt Leon Urbas Chair of Process Control Systems & Process Systems Engineering Group Technische Universität Dresden Dresden Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Waste and recycling material sorting is crucial for reducing environmental impact and promoting resource recovery. However, its complexity poses significant challenges, necessitating the development of effective sorting processes. Manual operation of these plants can be less efficient than automated systems. The first step toward automation is utilizing a Digital Twin, which combines fundamental principles and data-driven insights into the waste sorting process. To achieve this, the equipment involved in waste sorting plants can be analyzed in detail, focusing on operational settings and their impact on overall efficiency. Initially, a steady-state model of the plant is developed, followed by the implementation of advanced strategies like model predictive control. The model can be rigorously tested and refined using a case study on German post-consumer waste. The architecture of the Digital Twin, comprising various building blocks such as the modeling and simulation block, is being developed to transition away from manual operations. This Digital Twin aims to enhance sorting efficiency through offline and online optimization of operational set points, leading to a more sustainable and resource-efficient future. Through simulations and real-time data integration, a Digital Twin for the waste and recycling material process can aid with process design, fine-tuning, and plant automation.

关键词： process design Predictive models Real-time systems Digital twins Recycling Steady-state Optimization Manufacturing automation Sorting Predictive control

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A Review of Evaluation Metrics Algorithmic Used in Scholarly Research Recommender System 4

A Review of Evaluation Metrics Algorithmic Used in Scholarly...

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4th International Multidisciplinary Information Technology and engineering Conference, IMITEC 2024

作者： Ovono, Gerald Zuva, Travos Otunniyi, Temidayo Faculty of Applied and Computer Sciences Department of Computer South Africa VaalUniversity of Technology Faculty of Engineering and Technology Department of Process Control and Computer Systems South Africa

ISBN: (纸本)9798350387988

The exponential growth of academic publications has made scholarly research recommender systems indispensable tools for researchers. These systems rely on diverse evaluation metrics to assess their effectiveness and relevance. This paper provides a comprehensive review and analysis of these metrics, categorizing them into accuracy, ranking, diversity, user-centric, coverage, temporal, and computational metrics. By employing a mixed-methods approach, combining systematic literature review and empirical analysis, we identify the prevalence and application of these metrics across various scholarly domains such as literature, conferences, and reviewers. Our findings highlight the widespread use of traditional metrics like precision, recall, and Fl-score, while emphasizing the growing importance of novel metrics such as unexpectedness and serendipity, especially in literature and conference recommendations. We also underscore the domain-specific nature of metric selection, with user-centric evaluations more prominent in literature recommendations, and ranking-focused metrics dominant in conference and reviewer recommendations. Furthermore, the study reveals a significant gap in the use of temporal and computational metrics, suggesting key areas for future research. This review offers valuable insights for researchers and practitioners, guiding them in metric selection and highlighting potential directions for enhancing the effectiveness, adaptability, and user satisfaction of scholarly recommender systems. © 2024 IEEE.

关键词： Algorithms Evaluation Metrics Novelty Recommender systems Scholarly Research Serendipity

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Design of Supervisory Model Predictive control for HVAC systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort 23

Design of Supervisory Model Predictive Control for HVAC Syst...

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23rd International Conference on control, Automation and systems, ICCAS 2023

作者： Srisurapanon, Panithan Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Department of Electrical Engineering Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9788993215274

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge. © 2023 ICROS.

关键词： Model predictive control

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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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