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MAO-DBN based membrane fouling prediction

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10923-10939页

作者： Wang, Zhiwen Zhao, Yibin Shi, Yaoke Ling, Guobi College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou China

Due to the complexity of the factors influencing membrane fouling in membrane bioreactors (MBR), it is difficult to accurately predict membrane fouling. This paper proposes a multi-strategy of integration aquila optimizer deep belief network (MAO-DBN) based membrane fouling prediction method. The method is developed to improve the accuracy and efficiency of membrane fouling prediction. Firstly, partial least squares (PLS) are used to reduce the dimensionality of many membrane fouling factors to improve the algorithm's generalization ability. Secondly, considering the drawbacks of deep belief network (DBN) such as long training time and easy overfitting, piecewise mapping is introduced in aquila optimizer (AO) to improve the uniformity of population distribution, while adaptive weighting is used to improve the convergence speed and prevent falling into local optimum. Finally, the prediction of membrane fouling is carried out by utilizing membrane fouling data as the research object. The experimental results show that the method proposed in this paper can achieve accurate prediction of membrane fluxes, with an 88.45% reduction in RMSE and 87.53% reduction in MAE compared with the DBN model before improvement. The experimental results show that the model proposed in this paper achieves a prediction accuracy of 98.61%, both higher than other comparative models, which can provide a theoretical basis for membrane fouling prediction in the practical operation of membrane water treatment. © 2024-IOS Press. All rights reserved.

关键词： Bioreactors

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Bearing fault diagnosis method for unbalance data based on Gramian angular field

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Journal of Intelligent and Fuzzy Systems 2024年第1-2期47卷 45-54页

作者： Yu, Ping Li, Rong-Bin Cao, Jie Qin, Jun-Hua College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou China

In the application of deep learning-based fault diagnosis, more often than not, the network model could perform better with a balanced dataset input, whereby the number of fault data is equivalent to that of normal data. However, in the context of real-world applications, the number of fault data is generally insufficient compared to the normal data. In this study, a new approach for fault diagnosis in unbalanced data sets is proposed using the Gramian angular field (GAF) method. Firstly, the GAF method is employed to convert one-dimensional data into two-dimensional data, which enhances the feature extraction process. Secondly, to balance the sample distribution, fault data is generated using Generative Adversarial Networks (GANs). Finally, the Residual neural network (ResNet) with an attention mechanism is utilized to improve the accuracy of fault diagnosis. The proposed method is experimentally validated using open-source bearing datasets that are published by Case Western Reserve University and the University of Ottawa. The experimental results show that the proposed method has greatly improved fault diagnosis performance in cases of data distribution imbalance, surpassing that of the compared methods. © 2024 - IOS Press. All rights reserved.

关键词： Generative adversarial networks

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Data-driven output regulation control for constrained linear systems

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Science China(information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1617-1630页

作者： Yi Yang Peng Zhang Can Wang Zhuoli Zhao Loi Lei Lai the Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station College of Electrical Engineering and New EnergyChina Three Gorges UniversityYichangChina the Department of Electrical Engineering School of AutomationGuangdong University of TechnologyGuangzhouChina

The traditional energy hub based model has difficulties in clearly describing the state transition and transition conditions of the energy unit in the integrated energy system(IES).Therefore,this study proposes a state transition modeling method for an IES based on a cyber-physical system(CPS)to optimize the state transition of energy unit in the *** method uses the physical,integration,and optimization layers as a three-layer modeling *** physical layer is used to describe the physical models of energy units in the *** the integration layer,the information flow is integrated into the physical model of energy unit in the IES to establish the state transition model,and the transition conditions between different states of the energy unit are *** optimization layer aims to minimize the operating cost of the IES and enables the operating state of energy units to be transferred to the target *** simulations show that,compared with the traditional modeling method,the state transition modeling method based on CPS achieves the observability of the operating state of the energy unit and its state transition in the dispatching cycle,which obtains an optimal state of the energy unit and further reduces the system operating costs.

关键词： Integrated energy system(IES) cyber-physical system(CPS) state transition modeling optimal dispatching

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Path Planning for Data Collection Multiagent System with Priority and Moving Nodes in a Sensing Field with Obstacles

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2024年第3期68卷 309-318页

作者： Szénási, Sára Harmati, István Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok körútja 2 Budapest1117 Hungary

Nowadays there is a more and more common need for one-off data collection in a specified area. For example, in case of searching for the survivors of disasters or wars, or for skiers who get into trouble. The simplest way of collecting such data is using wireless sensor network (WSN). However, data transmission within the network uses great amount of energy that may significantly reduce the lifetime and operation time of the battery-operated sensors. For this reason, the data transfer between the given sensor nodes is carried out by robots. In order to minimize the latency of data collection, it is possible to use cooperating robots. It frequently occurs that one of the nodes requires more urgent visit than the other ones, for example, the serious injuries require urgent medical attendance. The sensor nodes can also be moved to collect more usable data in a larger field. To solve this, path planning for data collection from priority and moving nodes are also presented here. The algorithm developed here to perform the one-off data collection operates so that the agents start from preliminary determined or random points and then visit all the sensor nodes, download the data from these nodes and after this arrive at a designated point where they upload the collected information. The goal here is the minimization of cost that include not only the walk-through time but also the consequences of the late visit of the higher priority nodes. The optimization is solved using the ant colony optimization. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Motion planning

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Data-driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 874-885页

作者： Wenlong Liao Dechang Yang Qi Liu Yixiong Jia Chenxi Wang Zhe Yang Wind Engineering and Renewable Energy Laboratory Ecole Polytechnique Federale de Lausanne(EPFL)Lausanne 1015Switzerland the College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China the Department of Electrical and Electronic Engineering(Energy Digitalization Laboratory) The University of Hong KongHong KongChina the Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina

Reactive power optimization of distribution networks is traditionally addressed by physical model based methods,which often lead to locally optimal solutions and require heavy online inference time *** improve the quality of the solution and reduce the inference time burden,this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs(topology and power loads)and reactive power scheduling schemes of distribution networks,from a data-driven *** graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix,a customized loss function,and the use of max-pooling ***,a rulebased strategy is proposed to adjust infeasible solutions that violate *** results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load ***,its online inference time is significantly faster than traditional physical model based methods,particularly for large-scale distribution networks.

关键词： Reactive power optimization graph neural network distribution network machine learning data-driven

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Isolated Bipolar Modular Multilevel DC-DC Converter with Self-balancing Capability for Interconnection of MVDC and LVDC Grids

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 365-379页

作者： Jinmu Lai Xin Yin Yaoqiang Wang Lin Jiang Zia Ullah Xianggen Yin School of Electrical and Information EngineeringZhengzhou UniversityZhengzhou 450001China Department of Electrical Engineering and ElectronicsUniversity of LiverpoolLiverpoolUK State Key Laboratory of Advanced Electromagnetic Engineering and TechnologyHuazhong University of Scienceand TechnologyWuhan 430074China

Bipolar medium-voltage DC(MVDC)and lowvoltage DC(LVDC)grids have the advantages of flexible integration of distributed renewable-energy generation and reliable power *** order to achieve voltage conversion,power transfer,and electrical isolation for bipolar MVDC and LVDC grids,a high-power DC-DC converter is ***,this paper proposes an isolated bipolar modular multilevel DCDC converter(BiMMDC)with power self-balancing capability for interconnection of MVDC and LVDC *** proposed BiMMDC consists of two series connected MMCs in the MV stage to configure a bipolar MVDC interface,and interleaved converters combined with a dual-transformer are designed in the LV stage to configure the bipolar LVDC interface and to provide a self-balancing *** circuits of two series-connected MMCs and a dual-transformer with interleaved converters are *** that,operation principles of the proposed BiMMDC are introduced,considering balanced/unbalanced power transfer of bipolar LVDC grid and monopolar shortcircuit or open-circuit faults at MVDC *** control scheme is also presented for the proposed BiMMDC under different operating ***,a Matlab simulation and controller hardware-in-the-loop(CHIL)evaluation results are provided to validate the feasibility and effectiveness of the proposed typology and its operating performance.

关键词： Bipolar DC-DC converter equivalent circuit modular monopolar operation multilevel self-balancing

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Design of Double-Loop Current Transformer Based on Magnetic Field Incomplete Cancellation

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 772-782页

作者： Wenbo Li Xiaojun Tang Youshui Lu Ling Yan Yi Wu Mingzhe Rong Department of Measurement and Control Technology&Instrumentation School of Electrical EngineeringXi'an Jiaotong UniversityXi'an 710000China State Key Laboratory of Electrical Insulation&Power Equipment School of Electrical EngineeringXi'an Jiaotong UniversityXi'an 710000China

Electromagnetic current transformer is one of the important pieces of equipment used in AC power system measurement. Due to continuous improvement of current level to be measured in the power system, ordinary single-loop magnetic core structure cannot meet industrial needs of wide measuring range with high accuracy, while it even has a magnetic saturation problem when measured current is reaching the limit. Most existing methods expand measuring range and increase antisaturation ability of the magnetic core by either opening an air gap in the magnetic core or increasing number of turns of primary and secondary windings, but it will bring additional problems such as volume and heat dissipation of the transformer. To solve such issues, in this paper, we proposed a magnetic core structure of double-loop current transformer based on incomplete magnetic field cancellation principle. Calculation formula of air gap size and theoretical error are analyzed. We provide a theo-retical analysis of working characteristics, amplitude error and phase error throughout a three-dimensional simulation model of transformer. In addition, we evaluate performance through a series of comparison experiments. Results demonstrate our double-loop current transformer can maintain good linear relationship between primary and secondary current while ensuring measurement accuracy at 0.2 level. With the same volume, it has a wider range of rated current measurements and a certain anti-saturation ability.

关键词： Current difference coefficient double-loop core incomplete magneticfield cancellation

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Robust Trajectory Tracking control of a Differentially Flat Overhead Crane Using Sliding Mode

Periodica polytechnica Electrical engineering and computer s...

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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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Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and Computer Science 2024年第4期68卷 319-326页

作者： Arató, Péter Markovits, Tibor Gergely Rácz, György Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units. © 2024 Budapest University of technology and Economics. All rights reserved.

关键词： Distributed parameter control systems

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