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State estimation for a large-scale wastewater treatment system

AUTOMATICA 1996年第3期32卷 305-317页

作者： Tenno, R Uronen, P Lab. of Proc. Control and Management Helsinki University of Technology SF-02150 Espoo Kemistintie 1 Finland

A new distributed parameter stochastic model is introduced for modelling a large-scale wastewater treatment system with distributed water feeding, sludge recycling and removal. The state estimation problem is formulated as a biomass and organic matter profile estimation problem for the aeration basin. It is solved by approximation of the original model with a finite-dimensional bilinear model and the filtration distribution with the normal distribution. It is shown that the profile can be estimated online using dissolved oxygen and gas analysis results measured from several points over the aeration basin. The estimation quality is higher in the case of a large-scale aeration basin than in the case of a completely mixed basin. The estimation algorithm is obtained in a computationally effective form. The model and the estimation algorithm are tested in a simulation experiment. It is demonstrated that the sludge and water distribution has a strong effect on treated water quality. The distribution is considered as a new control parameter. It can be used in practice for improvement of treatment proc.ss quality.

关键词： biotechnology wastewater treatment modelling distributed parameters partially observable stochastic system state estimation

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Fault diagnosis system for the Outokumpu flash smelting proc.ss

Fault diagnosis system for the Outokumpu flash smelting proc...

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EPD Congress 2001

作者： Jämsä-Jounela, S.-L. Kojo, I. Vapaavuori, E. Vermasvuori, M. Haavisto, S. Lab. of Proc. Control and Automation Helsinki University of Technology P.O. Box 6100 FIN-02015 HUT Finland

Fault diagnosis systems have attracted growing interest in a number of engineering fields. The number of applications has increased and successful results have been widely reported. The fault diagnosis system presented in this paper is integrated, and it monitors the states of the proc.ss and performs fault detection and diagnosis on the proc.ss equipment. The monitoring of proc.ss states is carried out by means of Kohonen Self-Organising Maps that is a powerful tool in visualisation and analysis of high dimensional data in engineering applications. This paper presents the results of SOM analysis carried out on the Outokumpu flash smelting proc.ss. The subsystems analyzed in more detail are the condition of the concentrate burner, the condition of the gas line on the basis of the pressure distribution in the proc.ss and the cooling water circulation of the waste heat boiler, and the condition of the furnace and furnace equipment on the basis of the temperature distribution in the furnace and gas line.

关键词： Smelting

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Hamilton-Jacobi-Bellman equations for Fuzzy-Dual Optimization 36

Hamilton-Jacobi-Bellman equations for Fuzzy-Dual Optimizatio...

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第36届中国控制会议

作者： Lunlong Zhong Felix Mora-Camino Hakim Bouadi Roger Marcelin Faye Key Lab. for Adv.Signal Proc. Civil Aviation University of China Automation Research Group ENACToulouse University

ISBN: (纸本)9781538629185

In this article, after introducing fuzzy-dual numbers, functions and functionals, the optimization of a fuzy-dual functional is considered through an extension of Euler’s condition. Then, once uncertainty is imbedded in a fuzzy-dual dynamical system, the optimization of such systems is considered, leading to an extended Hamilton-Jacobi-Bellman equation to characterize optimal fuzzy-dual solutions.

关键词： fuzzy-dual numbers uncertain systems Euler’s equation optimal control Hamilton-Jacobi-Bellman equation

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Stability analysis of networked control system

Stability analysis of networked control system

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proc.edings of 2002 International Conference on Machine Learning and Cybernetics

作者： Xie, Lei Zhang, Jian-Ming Wang, Shu-Qing National Key Lab. of ICT Research Inst. of Adv. Proc. Control Zhejiang University Hangzhou 310027 China

ISBN: (纸本)0780375084

An alternative problem statement of Networked control System (i.e. NCS) is proposed and a stability criterion based on the new problem statement is discussed. With this stability criterion, we are able to analyze the network transmission delay deadlines that guarantees stability. Compared with reported results, it's less conservative and more computationally effective.

关键词： control system analysis

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Application of model-based fault detection and diagnosis to the quality assurance of an automotive actuator

Application of model-based fault detection and diagnosis to ...

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Tutorial Workshop on Supervision, Fault Detection and Diagnosis of Technical Systems at the IFAC World Congress

作者： Pfeufer, T Institute of Automatic Control Lab. Contr. Eng. and Proc. Automat. Darmstadt University of Technology D-64283 Darmstadt Landgraf-Georg. Str. 4 Germany

The increased degree of automation of technical proc.sses requires an increased number of mechanical-electronic components. In order to maintain the dependability and availab.lity despite of the increased complexity, new methods for the quality assurance of mechanical-electronic systems are necessary. This paper describes an automatic diagnostic system for an automotive actuator. Analytic models of the proc.ss under investigation are used in order to extract detailed information about the proc.ss, using only the usually measured signals and evaluating the signals e.g. by parameter estimation and state estimation. However, some relations, especially the cause - effect relations between the underlying faults and the observable symptoms, are quite difficult to represent by analytic models. A rule-based approach is more suitable to acquire, represent and proc.ss the diagnostic knowledge base. In order to cope with uncertainty, a fuzzy structure is applied to the classification of faults. Copyright (C) 1997 Elsevier Science Ltd.

关键词： approximate reasoning decision making fault detection fault diagnosis parameter estimation fuzzy supervision electromechanical actuators

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Trends in the application of model-based fault detection and diagnosis of technical proc.sses

Trends in the application of model-based fault detection and...

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作者： Isermann, R. Ballé, P. Institute of Automatic Control Lab. Contr. Eng. and Proc. Automat. Darmstadt University of Technology Landgraf-Georg.Str. 4 D-64283 Darmstadt Germany

After a short overview of the historical development of model-based fault erection, some proposals for the terminology in the field of supervision, fault detection and diagnosis are stated, based on the work within the IFAC SAFEproc.SS Technical Committee. Some basic fault-detection and diagnosis methods are briefly considered. Then, an evaluation of publications during the last 5 years shows some trends in the application of model-based fault-detection and diagnosis methods.

关键词： Error detection

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Weakly-supervised temporal action localization through local-global background modeling

arXiv

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arXiv 2021年

作者： Wang, Xiang Qing, Zhiwu Huang, Ziyuan Feng, Yutong Zhang, Shiwei Jiang, Jianwen Tang, Mingqian Shao, Yuanjie Sang, Nong Key Lab. of Image Proc. and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China

Weakly-Supervised Temporal Action Localization (WSTAL) task aims to recognize and localize temporal starts and ends of action instances in an untrimmed video with only video-level lab.l supervision. Due to lack of negative samples of background category, it is difficult for the network to separate foreground and background, resulting in poor detection performance. In this report, we present our 2021 HACS Challenge-Weakly-supervised Learning Track [24] solution that based on BaSNet [10] to address above problem. Specifically, we first adopt pre-trained CSN [17], Slowfast [5], TDN [19], and ViViT [1] as feature extractors to get feature sequences. Then our proposed Local-Global Background Modeling Network (LGBM-Net) is trained to localize instances by using only video-level lab.ls based on Multi-Instance Learning (MIL). Finally, we ensemble multiple models to get the final detection results and reach 22.45% mAP on the test set. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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System identification from small data sets using an output jittering method with application to model estimation of bioethanol production

System identification from small data sets using an output j...

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Yang, Jing Wei, Hua-Liang Kadirkamanathan, Visakan Lin, Xiaofang Key Lab. of Biofuels Inst. Bioengergy and Proc. Tech. Chinese Academy of Science Qingdao Shandong Province China Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD United Kingdom

ISBN: (纸本)9781467314855

A novel simple approach is presented for solving small sample size problem in nonlinear dynamic system identification where only a very small number of measured input and output data points are availab.e. The technique is built upon an orthogonal least squares algorithm and a new resampling method called output jittering method,. The proposed algorithm is applied to the model identification of bioethanol production and it shows that a robust and reliable model can be obtained with the new system identification approach. © 2012 IEEE.

关键词： Ethanol

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Evolutionary Dynamics of Cooperation on Coupled Networks 4

Evolutionary Dynamics of Cooperation on Coupled Networks

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4th International Conference on control Theory and Applications, ICoCTA 2024

作者： Shi, Zhenyu Su, Qi Shanghai Jiao Tong University Ministry of Education of China Key Lab. of Syst. Contr. and Info. Proc. Shanghai Eng. Res. Ctr. of Intelligent Contr. and Mgmt. Department of Automation Shanghai200240 China

ISBN: (纸本)9798331506155

Network reciproc.ty has been recognized as a crucial mechanism for promoting the evolution of cooperation. However, prior studies on network reciproc.ty have predominantly focused on isolated networks, neglecting the interconnected nature of real-world systems. In reality, many large-scale systems are closely coupled, where the interaction patterns between systems differ significantly from those within individual networks. Motivated by this observation, we construct a strategy evolution model on coupled networks to explore the effects of such interconnections. Our findings reveal that coupled networks foster cooperation more effectively than isolated networks. This advantage persists across various network structures, suggesting the universality of this phenomenon. Interestingly, we discover that the strength of the coupling plays a pivotal role: weaker coupling between networks is more conducive to the emergence and stability of cooperation compared to stronger coupling. These results high-light the importance of considering cross-system interactions in understanding and designing mechanisms to enhance cooperative behavior. © 2024 IEEE.

关键词： Cooperation Coupled networks Evolutionary game theory

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Research on Crop Disease and Pest Surveillance based on Big Data and Image proc.ssing Technologies

Research on Crop Disease and Pest Surveillance based on Big ...

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2024 International Conference on Information Technology, Communication Ecosystem and Management, ITCEM 2024

作者： Yang, Yimei Yang, Yujun Shu, Huixia Zhao, Changhua Deng, Shaowei Huaihua418008 China Hunan Provincial Key Laboratory of Ecological Agriculture Intelligent Control Technology Huaihua418008 China Key Lab. of Wuling-Mt. Hlth. Big Data Intelligent Proc. and Applic. in Hunan Province Universities Huaihua Hunan418000 China

ISBN: (纸本)9798331542696

Recently, with the increasing complexity of agricultural systems and climate change, agricultural pest and disease surveillance and early detection have become critical tasks for guaranteeing food stability and promoting sustainable farming growth. Agricultural pest and disease surveillance is a key component of agricultural production, directly affecting crop yield and quality. As big data advances and image proc.ssing technologies rapidly, their application in crop pest and disease surveillance has become increasingly widespread. By integrating multi-source data, such as remote sensing data, meteorological data, ecological data, and pest and disease survey data, researchers can build more accurate and efficient pest and disease surveillance models. This paper reviews the research progress of big data and image proc.ssing technologies in crop pest and disease surveillance, analyzes the advantages and challenges of current technologies, and proposes future research directions to enhance the automation and intelligence of systems. Additionally, it discusses the integration of deep learning and other techniques to achieve efficient information mining and accurate retrieval of disaster-related data, aiming to provide scientific guidance and technical support for agricultural production. © 2024 IEEE.

关键词： Big Data Analysis Image proc.ssing Technology Pest and Disease Detection

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