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control Parameter Optimization for a Longitudinal automatic Landing System via a Multi-objective Genetic Algorithm 5th

Control Parameter Optimization for a Longitudinal Automatic ...

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5th international conference on Aerospace System science and engineering, ICASSE 2021

作者： Chen, Cheng Ke, Jie Xu, Haonan Lu, Bei Li, Qifu Shanghai Jiao Tong University Shanghai China Shanghai Aircraft Design and Research Institute Shanghai China

ISBN: (纸本)9789811681530

It is challenging for control design and parameter optimization of a civil aircraft automatic landing system due to the complex application environment and high tracking precision requirement. In this paper, a parameter optimization method based on the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to reduce the workload of control gain tuning and improve the performance of the autoland system. To facilitate the eventual engineering application, the flying quality indices are explicitly considered when defining the objective function for optimization. The proposed method is applied to design a longitudinal automatic landing system. It greatly simplifies the design process, and simulation results also demonstrate the effectiveness of the method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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Research on automatic Generation and Verification of Test Sequence for New Train control System 1

引用

2nd international conference on Information control, electrical engineering and Rail Transit, ICEERT 2022

作者： Zang, Yuanshan Li, Kaicheng Li, Chenyue Yuan, Lei Liu, Yu Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China China Railway Information Technology Center Beijing100044 China

ISBN: (数字)9789819964314

ISBN: (纸本)9789819964307

Aiming at efficiency and correctness of test sequences generation, we propose a method to automatically generate test sequences and verify their correctness. First, we design an automatic test sequence generation method based on the BERT model, which is used to learn the context between test cases to automatically generate test sequences. Second, we design a method to judge the correctness of test sequences based on the rule engine. The Named Entity Recognition (NER) is used to extract information from domain documents. We design a rule extraction algorithm to realize the automatic construction of the Rule Base. Then, we complete the correctness verification of test sequences based on Drools rule engine. Experimental results show that this method can automatically generate high-quality test sequences, and effectively verify the correctness of test sequences. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Black-box testing

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Low-Power Variable-Gain CMOS Trans Impedance Amplifier for Near Infra-Red Spectroscopy Applications

Low-Power Variable-Gain CMOS Trans Impedance Amplifier for N...

引用

2023 international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2023

作者： Muthukumaran, B. Ramachandran, B. SRM Institute of Science and Technology College of Engineering and Technology Department of Electronics and Communication Engineering Kattankulathur India

ISBN: (纸本)9798350319200

A novel low-power and variable gain CMOS Trans Impedance Amplifier (LP-VG-TIA) circuit design for Near Infra-Red Spectroscopy (NIRS) Applications is presented in this paper. The proposed low power and variable gain CMOS Trans Impedance Amplifier achieves a variable gain from 55.06 dB to 119.81 dB with a minimum bandwidth of 12.46 MHz and a maximum bandwidth of 25.33 MHz. The variable gain control is used to achieve different values of the gain and the bandwidth for multiple bio-medical sensor applications. The input-referred noise with photodiode (PD) model with 1pF capacitance is 1.6pArms. The maximum input photocurrent is 1uAp-p. The proposed LP-VG-TIA consumes 95.3 μW at a room temperature of 27 °C from a 1V power supply. The proposed circuit has been implemented using a GPDK 45nm CMOS process. The proposed low power and variable gain TIA outperforms the existing TIAs in the literature. © 2023 IEEE.

关键词： Analog-to-Digital Converter CMOS Amplifier Gain Bandwidth Product Low Power Near Infra-Red Spectroscopy Photodiode SNR TIA Variable Gain

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Design and Power Flow control in Standalone PV System with Reduced Battery Current Ripple

Design and Power Flow Control in Standalone PV System with R...

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2023 international conference on Power, Instrumentation, control and computing, PICC 2023

作者： Masoom, Md. Modassir Kumar, Narendra Kumar, Mayank Evrt Delhi Technological University Electrical Engineering Department Delhi India

ISBN: (纸本)9798350334463

To improve solar photovoltaic (PV) panel efficiency, maximum power point tracking (MPPT) algorithm is needed, which could help to extract the optimal power from solar PV systems. The adaptive backstepping controlling approach is presented in this paper for tracking maximum power points in PV systems. The controller is based on the Lyapunov stability theory and connects the selection of an appropriate Lyapunov function with the design of feedback control action. The reference voltages which are generated for the controller are generated through the maximum power voltage (MPV) searching algorithm. The battery energy storage system (BESS) is linked to a bidirectional converter, which governs both the DC bus voltage and the power flow from the BESS. The operation of the DC microgrid is addressed under varying irradiance changes. Further, the impact of ripple current on the battery heating and its performance are discussed. MATLAB/Simulink software is used to simulate and validate the effectiveness of a BESS-enabled isolated solar PV-based system. © 2023 IEEE.

关键词： controllers

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Smart Monitoring and Diagnostics for Fault Detection in Power Plant Equipment 3

Smart Monitoring and Diagnostics for Fault Detection in Powe...

引用

3rd IEEE international conference on Distributed computing and electrical Circuits and Electronics, ICDCECE 2024

作者： Kala, S. Padma Kumar S, Pradeep Meerimatha, G. Almusawi, Muntather Gurumoorthy, Sasikumar Dept Of Cse Tamilnadu Chennai India Nitte Meenakshi Institute Of Technology Department Of Ece Bengaluru India Department Of Eee Ananthapuramu India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq School Of Engineering And Technology Dhanalakshmi Srinivasan University Computer Science And Engineering Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9798350318609

In recent years, Fault Diagnosis and Identification (FDI) has grown significantly. Generally used methodology in these types of frameworks include model-based approaches, fault approaches, and pattern recognition techniques. However, it was essential to society's energy supply, therefore maintaining its safe and effective functioning is of utmost importance. This research used sophisticated Fault Detection and Diagnosis (FDD) methods to diagnose the problems in contemporary power plants in order to decrease maintenance shutdowns and expenses. Therefore, this research applied deep learning to image processing using efficient Long Short-Term Memory (LSTM)-based methods for object recognition and categorization. Using the observed frequency as input, the trained LSTM is utilized to detect power variations in real time. control devices, such as synchronous generators and Energy Storage Systems (ESSs), was maintain a steady frequency by using the detected power variations. According to the results, the suggested approach demonstrated superior performance in terms of LG faults, with 0.427%, LLG faults of 0.800%, LGG faults of 0.186 %, and LL faults of 0.741%. Compared with existing methods namely Sparrow Search Algorithm (SSA) and Deep Long Short-Term Memory (LSTM) it shows that suggested methods are achieved better performances with less faults respectively. © 2024 IEEE.

关键词： Long short-term memory

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Design and Development of Multi-Terminal USV Remote control System Based on LoRa WAN 6

Design and Development of Multi-Terminal USV Remote Control ...

引用

6th international conference on computing, Electronics and Communications engineering, iCCECE 2023

作者： Luo, Yichen Lin, Wenhao Wei, Haiyu Zhu, Yiran Huang, Youyang Zhu, Xiaohui Yue, Yong Ma, Jieming Xi'An Jiaotong-Liverpool University School of Advanced Technology Suzhou China University of Liverpool School of Electrical Engineering Electronics and Computer Science Liverpool United Kingdom

ISBN: (纸本)9798350340921

This paper presents a novel multi-Terminal remote control system for Unmanned Surface Vehicles (USVs) utilizing LoRa technology. The proposed system includes a remote controller, mobile APP, Data Transfer Unit (DTU) for ground-side and USV-side. The system realizes bidirectional data transmission from the USVs to the ground station, and the communication distance is greatly improved compared with the traditional 2.4GHz remote control, which overcomes the defect of insufficient communication distance of traditional remote control for USVs caused by the interference of water reflection. In addition, our system also supports smart devices such as mobile phones and computers to participate in the cooperative remote control of USVs, making the control of USVs more convenient and flexible. Experimental results show that when the data transmission frequency of the DTU for gorund-side and USV-side is 0.1s and 2s respectively, the packet loss rate is about 3.28%, and the system has low communication delay and high flexibility, which meets our requirements. © 2023 IEEE.

关键词： Remote control

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A Hybrid Approach for Facial Expression Detection using Principal Component Analysis and Feature Extraction 7

A Hybrid Approach for Facial Expression Detection using Prin...

引用

7th international conference on Intelligent computing and control Systems, ICICCS 2023

作者： Goyal, Shefali Singh, Nongmeikapam Thoiba Dhiman, Tanu Chandigarh University Department of Computer Science Engineering Punjab India

ISBN: (纸本)9798350397253

A number of systems have been proposed to deal with the issue of automatic emotion detection from facial images. The challenges in this field of research are enormous. The face complexion of different persons belongs to different regions of the globe, different facial accessories, and different poses are further made the detection challenging. A facial expression detection system has been proposed based on a principal component analysis (PCA) approach and feature-based technique (FBT). The system considered four categories of emotions: happy, normal, surprising, and sad. Overall recognition accuracy achieved is 98.09%. The proposed approach can be further enhanced for use in the detection of other emotion categories as well. © 2023 IEEE.

关键词： Principal component analysis

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Redefining Tea Cultivation: A Federated Approach to Detecting Leaf Diseases with CNN 4

Redefining Tea Cultivation: A Federated Approach to Detectin...

引用

4th international conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Suryavanshi, Ankita Kukreja, Vinay Bordoloi, Dibyahash Mehta, Shiva Choudhary, Ankur Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350343670

Tea leaf diseases have become a significant problem in the vast field of agricultural research, calling for sophisticated diagnostic methods. This research takes a cutting-edge approach, carefully classifying tea leaf illnesses using the power of Federated Learning combined with Convolutional Neural Networks (CNN). This research project included records from six customers, each representing four levels of illness severity. The research eliminated the requirement for centralized data aggregation by using the decentralized architecture of federated learning to permit collaborative but privacy-preserving data analysis. The Federated Averaging CNN Result Analysis reveals fascinating results. The Macro averages varied from a spectacular 88.66% (Z_2) to 93.35% (Z_4). Similar patterns emerged from weighted averages, with the zenith recorded at 93.46% (Z_4) and the nadir at 89.57% (Z_2). The weighted average numbers for customers like Z_4 and Z_5, which came in at 93.46% and 92.67%, were mirrored by the Micro averages, reflecting a holistic performance view. Such uniformity across several criteria highlights the model's flexibility and resilience. In conclusion, this landmark study clarifies the enormous potential of CNNs and Federated Learning to revolutionize the detection of tea leaf illness. The consistently high statistical results across various clients and severity levels herald a new era in precision agriculture, promising improved disease control and, consequently, healthier yields. © 2024 IEEE.

关键词： Convolutional neural networks (CNNs) Disease classification Federated learning Severity levels Tea leaf diseases

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Knowledge Distillation Boosted Ultra-light Weight Road Object Detection on Edge Device 6

Knowledge Distillation Boosted Ultra-light Weight Road Objec...

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6th IEEE international conference on Knowledge Innovation and Invention, ICKII 2023

作者： Chen, Duan-Yu Hsu, Yi-Wen Yuan Ze University Department of Electrical Engineering Taoyuan Taiwan

ISBN: (纸本)9798350323535

Road object detection is required for automatic driving and intelligent traffic control and detecting illegal behavior. However, many edge computing devices do not have high computing power. Therefore, it is necessary to deploy a lightweight object detection model while maintaining its performance. Thus, we developed a scenario on the 24-hour automatic patrol camcorder for the corners and alleys. The device instantly identified and detected suspicious vehicles or pedestrians and sent notifications. Hence, the model had low complexity and efficiency to meet the requirement of real-time detection. We improved the model's precision within the limited inference time. In the experiment, YOLOv5 was selected as the base model for lightweight model construction on the Snapdragon 660 Mobile Platform on Xiaomi Mi A2. The designed model YOLOv5p with parameter size 0.7 M boosted knowledge distillation from mean average precision (mAP) of 18 to 19.3% on the BDD100K dataset. © 2023 IEEE.

关键词： Object detection

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Hardware Designing of automatic Changeover for Single Phase Load 1

Hardware Designing of Automatic Changeover for Single Phase ...

引用

1st international conference on Intelligent controller and computing for Smart Power, ICICCSP 2022

作者： Gupta, Ankur Kumar Singh, Rishi Kumar Mitra, Uliya Maulana Azad National Institute of Technology Dept. of Electrical Engineering Bhopal India

ISBN: (数字)9781665472586

ISBN: (纸本)9781665472586

automatic changeover for single-phase load is an electrical control panel that can give uninterrupted power supply for single-phase load under fault conditions of any one of the phases in the system. It is capable to transfer the load from the main supply to the auxiliary supply during fault. This paper presents a prototype of automatic changeover of single-phase load. The control panel does not require any other secondary supply to operate itself. The panel consists of contactors, relay, timer, and add-ons on the contactor which are connected according to the logic made. The electrical control panel also acts as a secondary protection device for all electrical devices applied in the three phases. The control panel is a small step towards an uninterrupted power supply. This panel will increase the reliability of electricity. The prototype is having huge potential in the residential sector like big apartments and is also used for small scale industries. These automatic transfer switches are also used in large-scale industries to protect the devices because of power outages. © 2022 IEEE.

关键词： Outages

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