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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Pichardo-Almarza, César Smallwood, Rod Billings, S.A. Department of Computer Science University of Sheffield Sheffield United Kingdom Department of Automatic Control and System Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)1424415098

Agent-based models are widely used for the simulation of systems from several domains (biology, economics, meteorology, etc). In biology agent-based models are very useful for predicting the social behaviour of systems;in particular they seem well adapted to model the behaviour of a cell population. In this paper an agent-based model, developed to study normal human keratinocytes (tissue cells), will be investigated. This kind of model exhibits probabilistic behaviour and the validation of simulation results is often done with a qualitative analysis by the experts (biologists). The main objective of this paper is to propose new variables and metrics that allow the comparison and a possible quantitative validation using numerical results from simulations. ©2007 IEEE.

关键词： Cell culture

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Preventing Frequency Instability Using Large-Scale Photovoltaic Resources 8

Preventing Frequency Instability Using Large-Scale Photovolt...

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8th International Conference on Technology and Energy Management, ICTEM 2023

作者： Yari, Siavash Khoshkhoo, Hamid Rouzbehi, Kumars Emran, S. M. Ale Sahand University of Technology Faculty of Electrical Engineering Sahand Iran University of Seville Department of System Engineering and Automatic Control Seville Spain Faculty of Engineering Canada

ISBN: (纸本)9781665452854

Various control methods have been presented to prevent the occurrence of instability in power systems, among which, it seems that methods based on the special protection system (SPS) are more effective and efficient than other ones. In this article, a SPS using the capabilities of large-scale photovoltaic power plants (LSPVPPs) is presented to prevent frequency increase and instability in power systems. According to the presented algorithm, when frequency increases, the proposed SPS uses the ability of photovoltaic power plants to quickly change their generation powers based on the operating point and frequency changes to prevent frequency instability. To confirm the proposal, LSPVPPs along with their controllers are modeled in the DSL environment of DIgSILENT PowerFactory software. The proposed SPS is implemented and tested on the IEEE 39-bus test system and the results of dynamic simulations show that this SPS prevents frequency instability in different conditions by taking timely measures. © 2023 IEEE.

关键词： Electric power system protection

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Speed sensorless control with neuron MARS estimator of an induction machine

Speed sensorless control with neuron MARS estimator of an in...

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2006 2nd International Conference on Power Electronics systems and Applications, ICPESA

作者： Lei, Dong Dong, Yang Xiaozhong, Liao Department of Automatic Control Engineering Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

ISBN: (纸本)9623675445

In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MARS) for speed estimation are used to improve the perfornance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved perfornance in low speed range.

关键词： Induction machine

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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling

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Environment International 2025年 199卷 109496页

作者： Ahmed, Maqsood Zhang, Xiang Shen, Yonglin Ahmed, Tanveer Ali, Shahid Ali, Ayaz Gulakhmadov, Aminjon Nam, Won-Ho Chen, Nengcheng National Engineering Research Center of Geographic Information System School of Geography and Information Engineering China University of Geosciences Wuhan430074 China Department of Computer Science School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Software College Northeastern University Shenyang110169 China Department of Cybernetics Nanotechnology and Data Processing Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Research Center of Ecology and Environment in Central Asia Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi830011 China Institute of Water Problems Hydropower and Ecology of the National Academy of Sciences of Tajikistan Dushanbe734042 Tajikistan School of Social Safety and Systems Engineering Institute of Agricultural Environmental Science National Agricultural Water Research Center Hankyong National University Anseong Korea Republic of

Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on single static image analysis, which does not account for the dynamic and temporal nature of air pollution. Meanwhile, research on video-based air quality estimation remains limited, particularly in achieving accurate multi-pollutant outputs. This study proposes Air Quality Prediction-Mamba (AQP-Mamba), a video-based deep learning model that integrates a structured Selective State Space Model (SSM) with a selective scan mechanism and a hybrid predictor (HP) to estimate air quality. The spatiotemporal forward and backward SSM dynamically adjusts parameters based on input, ensures linear complexity, and effectively captures long-range dependencies by bidirectional processing of spatiotemporal features through four scanning techniques (row-wise, column-wise, and their vertical reversals), which allows the model to accurately track pollutant concentrations and air quality variations over time. Thus, the model efficiently extracts spatiotemporal features from video and simultaneously performs regression (PM2.5, PM10, and AQI), and classification (AQI) tasks, respectively. A high-quality outdoor hourly air quality dataset (LMSAQV) with 13,176 videos collected from six monitoring stations in Lahore, Pakistan, was utilized as the case study. The experimental results demonstrate that the AQP-Mamba significantly outperforms several state-of-the-art models, including VideoSwin-T, VideoMAE, I3D, VTHCL, and TimeSformer. The proposed model achieves strong regression performance (PM2.5: R2 = 0.91, PM10: R2 = 0.90, AQI: R2 = 0.92) and excellent classification metrics: accuracy (94.57 %), precision (93.86 %), recall (94.20 %), and F1-score (93.44 %), respectively. The proposed model delivers consistent, real-time performance with a latency

关键词： Air quality

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Real-time Image Identification for Vehicle Positioning system 4

Real-time Image Identification for Vehicle Positioning Syste...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Liu, Chun-Yu Huang, Ching-Huei Juang, Rong-Terng Feng Chia University Department of Automatic Control Engineering Taichung City Taiwan Institute of Aerospace and System Engineering Taipei Tech Taipei City Taiwan

ISBN: (纸本)9798350360721

An innovative vehicle real-time positioning method was developed to maximize the use of existing visible light camera systems on vehicles, especially in areas without Global Positioning system (GPS) signals or blind spots. This approach eliminates the need for additional positioning devices and leverages the potential of existing vehicle driver assistance systems. As vehicles are equipped with cameras for monitoring the surrounding environment, we optimized the use of these existing resources for an efficient and accurate innovation in vehicle positioning. Firstly, we used cameras in four directions (the front, rear, left, and right) of the vehicle to capture images. By integrating images in four directions and using a transformation algorithm, a complete top-down view was formed with geographic information to enhance positioning accuracy. The integrated top-down view image is useful for obtaining information on surrounding environments and identifying the vehicle's real-time location in parking lots. The developed method serves as a foundation for future applications in automated driving planning and positioning. © 2024 IEEE.

关键词： Global positioning system

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Finite state control of FES-assisted walking with spring brake orthosis

Finite state control of FES-assisted walking with spring bra...

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2011 UKSim 13th International Conference on Modelling and Simulation, UKSim 2011

作者： Jailani, R. Tokhi, M.O. Gharooni, S.C. Jogtaei, M. Department of Automatic Control and System Engineering University of Sheffield United Kingdom Faculty of Electrical Engineering Universiti Teknologi MARA 40450 Shah Alam Malaysia

ISBN: (纸本)9780769543765

This paper presents finite state control (FSC) of paraplegic walking with wheel walker using functional electrical stimulation (FES) with spring brake orthosis (SBO). The work is a first effort towards restoring natural like swing phase in paraplegic gait through a new hybrid orthosis, referred to as spring brake orthosis (SBO). This mechanism simplifies the control task and results in smooth motion and more-natural like trajectory produced by the flexion reflex for gait in spinal cord injured subjects. The study is carried out with a model of humanoid with wheel walker using the Visual Nastran (Vn4D) dynamic simulation software. Stimulated muscle model of quadriceps is developed for knee extension. Fuzzy logic control (FLC) is developed in Matlab/Simulink to regulate the muscle stimulation pulse-width required to drive FES-assisted walking gait and the computed motion is visualised in graphic animation from Vn4D and finite state control is used to control the transaction between all walking states. Finite state control (FSC) is used to control the switching of brakes, FES and spring during walking cycle. © 2011 IEEE.

关键词： Brakes

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Evaluation of Theoretical and Empirical Log-Normal Models for Wi-Fi Fingerprint Mapping in Indoor Positioning 6

Evaluation of Theoretical and Empirical Log-Normal Models fo...

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6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Bin Mohamed Ghazali, Mohamed Aizad Kiring, Aroland Mihaylova, Lyudmila Yew, Hoe Tung Chung, Seng Kheau Farm, Yan Yan Faculty of Engineering Universiti Malaysia Sabah Sabah Kota Kinabalu Malaysia University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom

ISBN: (纸本)9798350389692

This paper evaluates both the theoretical and empirical log-normal models for Wi-Fi fingerprint mapping in indoor positioning systems. Wi-Fi fingerprinting, leveraging the ubiquitous IEEE 802.11 protocol, offers a practical solution for indoor localization where Global Positioning system (GPS) is ineffective. It involves generating empirical data by systematically measuring Wi-Fi Received Signal Strength (RSS) within a complex indoor environment and formulating a log-normal path loss model to predict signal behavior. A comparative analysis was conducted between the theoretical model, calibrated with empirical RSS data, and the actual RSS measurements. The results showed that while the theoretical model captured overall signal propagation trends, the empirical data revealed variations due to multipath effects and environmental obstacles. It demonstrated the practical use of Wi-Fi fingerprint mapping, theoretical modeling, and comparative analysis. The findings underscore the importance of empirical validation in refining theoretical models and optimizing deployment strategies for accurate and reliable indoor positioning. Future research should focus on mitigating multipath effects and enhancing the theoretical model accuracy through optimized access point (AP) placement and advanced signal processing techniques. © 2024 IEEE.

关键词： Global positioning system

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Robust control of nonlinear processes using multiple models 15th

Robust control of nonlinear processes using multiple models

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15th World Congress of the International Federation of automatic control, 2002

作者： Constantin, Nicolae Dumitrache, Ion Automatic Control and System Engineering Department University Politehnica Bucharest Spl. Independentei nr. 313 Bucharest77206 Romania

ISBN: (纸本)9783902661746

This paper addresses the problem of controlling a nonlinear process when linear models have been identified at different operating points. A multimodel approach is used to to identify and contro l highly nonlinear process. The internal linear model representation of the nonlinear plant for conventional robust controller is replaced by the linear parameter varying (LPV) model, which introduces transparency while offering distinct advantages for nonlinear model-based control. For this LPV structure a robust controller is then designed based on H∞ techniques. Simulation results for a CSTR process are used to illustrate the performance benefits of multimodel approach. Copyright © 2002 IFAC.

关键词： Process control

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Adaptive control based on neural fuzzy inference network 6

Adaptive control based on neural fuzzy inference network

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6th European control Conference, ECC 2001

作者： Dumitrache, I. Constantin, N. Automatic Control and System Engineering Department University Politehnica Bucharest Spi. Independentei nr.313 Bucharest77206 Romania

ISBN: (纸本)9783952417362

The long training time of multilayered backpropagation neural networks (BPNN) represents a serious drawback for the applications in industry. Moreover when they are trained on-line to adapt to plant variations, the overtuned phenomenon occurs. In this paper a novel neural fuzzy network (NFN) it is proposed which is suitable for adaptive control. The NFN represent a modified Takagi-Sugeno-Kang (TSK) type fuzzy rule based model with neural network learning ability. The rules are created and adapted in an online learning algorithm. The structure learning together with the parameter learning forms the learning algorithms for the neural fuzzy network. It is proved that NFN can greatly reduce the training time, avoid the over-tuned phenomenon and has perfect regulation ability. © 2001 EUCA.

关键词： Fuzzy inference

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Intermittent fault diagnosis based on EMD decomposition and convolutional neural network 2

Intermittent fault diagnosis based on EMD decomposition and ...

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2nd IEEE International Conference on Electrical, Automation and Computer engineering, ICEACE 2024

作者： Peng, Yu Liu, Yuhang Lin, Ruishi Xiang, Gang Wang, Shenhang Yang, Zhiming Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China Harbin Institute of Technology School of Electronics and Information Engineering Harbin China

ISBN: (纸本)9798350368208

The paper introduces an intermittent fault diagnosis method for analog circuits using EMD and CNN. The proposed method obtains the circuit output characteristics under different intermittent fault type using SPICE simulation. Then, EMD is used to extract the features and finally, the CNN model for fault detection and localization is built. The effectiveness of the method is validated through experiments in a three-phase SVPWM circuit. © 2024 IEEE.

关键词： Convolutional neural networks

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