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Recent Advancement in Autonomous Vehicle and Driver Assistance Systems

Recent Advancement in Autonomous Vehicle and Driver Assistan...

引用

2023 IEEE international Students' conference on electrical, Electronics and Computer science, SCEECS 2023

作者： Mishra, Abhishek Purohit, Jahanvi Nizam, Maruf Gawre, Suresh Kumar Maulana Azad National Institute of Technology Department of Mechanical Engineering MP Bhopal India Maulana Azad National Institute of Technology Department of Computer Science & Engineering MP Bhopal India Maulana Azad National Institute of Technology Department of Electrical Engineering MP Bhopal India

ISBN: (纸本)9798350398748

In past two decades, the popularity and use of autonomous vehicles and driver assistance systems has accelerated due to the advancement in artificial intelligence techniques, big data analysis, machine learning, computer vision, smart sensors and Internet of Things (IoT). Autonomous vehicles (AVs) are gaining popularity because it reduces traffic congestion along with increase in safety and fuel efficiency. The present paper focuses on the functionality of the driver-less car and Advanced Driver & Driving Assistance Systems (ADDAS). Driver assistance systems help drivers to driving safely by avoiding and minimising distractions by observing their actions. Artificial Intelligence can be incorporated when AVs drive alongside human-driven vehicles (HVs), also known as the era of Mixed Autonomy. The Markov decision process (MDP) can be used to represent the communication between the driver-less vehicles and the surroundings, where, MDP is a discrete-time imaginary command process. MDP is utilized in various fields like automation, economics, manufacturing, and automatic control. This paper provides a detailed review on recent research and developments on autonomous vehicles and ADDAS. Some onfield examples of ADDAS are automatic Parking, automatic Braking System (ABS), Blind Spot Monitors, Adaptive Cruise control (ACC), etc. © 2023 IEEE.

关键词： Autonomous vehicles

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An Analysis of Frequency Response in Integrated Power System Using Power Electronics controller Tuned With Whale Optimization Technique 3

An Analysis of Frequency Response in Integrated Power System...

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3rd international conference on Smart Technologies and Systems for Next Generation computing, ICSTSN 2024

作者： Ganguly, Somnath Choi, Joon-Ho Mudi, Joyti Kundu, S. Roy, Aloke Kumar Mukherjee, V. Chonnam National University Department of Electrical Engineering Gwangju Korea Republic of Bankura Unnayani Insstitute of Engineering West Bengal Bankura India Bankura Unnayani Institute of Engineering Department of Electrical Engineering West Bengal Bankura India Bharat Institute of Engineering and Technology Dept. of EEE Hyderabad India Bankura Unnayani Institute of Engineering Department of Computer Science and Engineering West Bengal Bankura India Indian Institute Technology Indian School of Mines Department of Electrical Engineering Jharkhand Dhanbad India

ISBN: (纸本)9798350391565

The performance of any isolated hybrid power system is characterized by the type of controller being used. The considered power generating units are the solar thermal power plant (STPP), wind turbine generator (WTG), and diesel engine generator (DEG), whose frequency stabilization has been done with the utilization of proportional-integral-derivative (PID), integral-tilt-derivative (I-TD), and tilt-integral-derivative (TID) controllers. Tuning controller gains using the whale optimization algorithm (WOA) and the quasi-oppositional based whale optimization algorithm (QOWOA) involves optimizing the parameters to achieve the best performance for a given hybrid system. A comparative frequency response of the system under the individual influence of PID, TID, and I-TD controllers has been shown with different types of load perturbations. The simulation result shows that QOWOA-TID outperforms the other controllers. The study addresses the critical need for optimizing control strategies in hybrid power systems to ensure stability, efficiency, and reliability, thereby contributing to the advancement of sustainable energy solutions. © 2024 IEEE.

关键词： Diesel engines

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Research on dynamic weighing of rare earth oxide based on Kalman-PSO-BP Neural network 5

Research on dynamic weighing of rare earth oxide based on Ka...

引用

5th international conference on Mechanical engineering, Intelligent Manufacturing, and Mechatronics, MEIMM 2024

作者： Zhao, Guoyu Liu, Shiqi Xu, Jinyong Li, Chenhui Liu, Xiaobo Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781510686786

ISBN: (纸本)9781510686779

Molten salt electrolysis is currently a commonly used method for the preparation of rare earth metals, and in order to improve the electrolysis efficiency and product purity, automated equipment is gradually replacing manual operation. The molten salt electrolysis process requires strict control of the temperature in the electrolysis tank, so it is necessary to control the quality of each rare earth oxide discharging. However, the vibration and noise interference during the operation of the equipment leads to dynamic weighing errors. To improve the dynamic weighing accuracy, Kalman filtering and Particle Swarm Optimization(PSO) were combined with Back propagation Neural Network (BP) to obtain the dynamic weighing data of six working conditions by the rare earth oxide automatic discharging equipment. The Kalman-PSO-BP model was constructed and trained by Matlab, and simulations showed that the model error was reduced by 55.9%, 52.6%, 47.2%, 52.9%, 53.7%, and 53.2% compared to the original error. © 2024 SPIE.

关键词： Kalman filters

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Data-Driven Dynamic Event-Triggered Sliding-Mode Heading control for Unmanned Surface Vehicles with Uncertainties

Data-Driven Dynamic Event-Triggered Sliding-Mode Heading Con...

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2024 IEEE international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Huarong Shan, Jinjun Li, Xing Yu, Hongnian School of Internet of Things Engineering Jiangnan University Wuxi214122 China York University Department of Earth and Space Science and Engineering TorontoONM3J 1P3 Canada School of Electrical Engineering and Intelligentization Dong-guan University of Technology Dongguan523000 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110819 China School of Computing Engineering and the Built Environment Edinburgh Napier University EdinburghEH10 5DT United Kingdom

ISBN: (纸本)9781665410205

This paper investigates a data-driven dynamic event-triggered sliding mode heading control problem for un-manned surface vehicles with uncertain dynamics models. First, a virtual sensor is introduced to establish a compact dynamic linearization model for the unmanned surface vehicle. Then, a dynamic event-triggered scheme is developed to alleviate the communication burden. Moreover, a sliding mode surface is designed, and a data-driven dynamic event-triggered sliding mode heading control approach is formulated. Finally, rigorous mathematical proofs are given, and several simulations demon-strate the effectiveness and superiority of the proposed method compared to existing approaches. © 2024 IEEE.

关键词： Sliding mode control

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Operation with Auxiliary Devices of automatics U sing External computing Resources on Trusted control Systems

Operation with Auxiliary Devices of Automatics U sing Extern...

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2023 international Ural conference on electrical Power engineering, UralCon 2023

作者： Nezhmetdinov, R. Nezhmetdinova, R. Utarbaev, R. Moscow State Technologycal University 'STANKIN' Moscow Russia

ISBN: (纸本)9798350303391

The possibility of controlling auxiliary devices of electroautomatics of technological equipment with the use of external computing resources on trusted control systems is considered. The method of identification of the user of technological equipment using a single-board computer and RFID (Radio-Frequency Identification) tags is proposed. For realisation of the specified method the structural scheme of the system of safety control for the machine tool with numerical control on the basis of single-board computer Raspberry Pi and RFID-reader is offered. Based on the structural scheme of the solution, the Architectural model of the access control system software is developed. The access control system connected to the CNC system AxiOMA control, developed at the Department of Computer control Systems, FGBOU VO 'MSTU 'STANKIN', is implemented in the work. © 2023 IEEE.

关键词： Computer control systems

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2023 3rd international conference on electrical engineering and control science, IC2ECS 2023

2023 3rd International Conference on Electrical Engineering ...

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3rd international conference on electrical engineering and control science, IC2ECS 2023

ISBN: (纸本)9798350382426

The proceedings contain 322 papers. The topics discussed include: electromagnetic design of 10kV high voltage induction motor based on Ansoft Maxwell;efficiency promotion strategy for three-level ANPC-DAB-based DC-DC converter with wide-range multi-objective optimization method;nonlinear data classification of power Internet of Things considering transient and steady state;analysis of early warning indicators for high voltage power cable tunnel fire based on experimental data;real-time evaluation model construction of GIS conductor thermal state based on PSO-BP neural network;research and application of CPS-based automatic circulation system for the entire silk production process;and transmission line relay protection fault-tolerant information sharing and joint analysis method.

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Octopus: Experiences with a Hybrid Event-Driven Architecture for Distributed Scientific computing

Octopus: Experiences with a Hybrid Event-Driven Architecture...

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2024 Workshops of the international conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Pan, Haochen Chard, Ryan Zhou, Sicheng Kamatar, Alok Vescovi, Rafael Hayot-Sasson, Valerie Bauer, Andre Gonthier, Maxime Chard, Kyle Foster, Ian Southern University of Science and Technology Department of Computer Science China Illinois Institute of Technology Department of Computer Science ChicagoIL United States University of Chicago Department of Computer Science ChicagoIL United States Argonne National Laboratory Data Science and Learning Division LemontIL United States

ISBN: (纸本)9798350355543

Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting distributed research infrastructures by enabling the organization, communication, processing, reliability, and security of events generated from many sources. To support the development of scientific EDA, we introduce Octopus, a hybrid, cloud-to-edge event fabric designed to link many local event producers and consumers with cloud-hosted brokers, and to provide a fabric for developing resilient applications. Octopus can be scaled to meet demand, permits the deployment of highly available Triggers for automatic event processing, and enforces fine-grained access control. We identify requirements in self-driving laboratories, scientific data automation, online task scheduling, epidemic modeling, and dynamic workflow management use cases, and present results demonstrating Octopus' ability to meet those requirements. Octopus supports producing and consuming events at a rate of over 4.2 M and 9.6 M events per second, respectively, from distributed clients. © 2024 IEEE.

关键词： Event-driven architecture research automation scientific computing

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Automated Drone Fault Detection Approach in Thrust Mode State

Automated Drone Fault Detection Approach in Thrust Mode Stat...

引用

2023 IEEE international conference on automatic control and Intelligent Systems, I2CACIS 2023

作者： Ghazali, Mohamad Hazwan Mohd Rahiman, Wan Novaliendry, Dony Risfendra Universiti Sains Malaysia Engineering Campus School of Electrical and Electronic Engineering Nibong Tebal14300 Malaysia Universitas Negeri Padang Faculty of Engineering Padang Indonesia

ISBN: (纸本)9798350321302

In recent years, there has been considerable interest in drones due to their flexibility and decreasing price. Drones are made up of electrical and mechanical components, and failure in these components might deteriorate the drone's performance and, worse, lead it to crash. In this study, fault detection approaches based on raw vibration and acoustic parameters were introduced. Motor failure and loose screws are simulated to represent electrical and mechanical faults. Based on the raw data obtained from the MEMS sensors, motor failure can be successfully detected by both approaches. The mechanical fault is difficult to be detected by the raw data of both approaches as the amplitude values recorded are close to the normal drone condition. These approaches are suitable to be applied in detecting motor failure compared to mechanical faults. © 2023 IEEE.

关键词： Fault detection

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A Novel automatic Carrier Landing System with ADRC-Based controller and LSTM-Based Compensation Method 3rd

A Novel Automatic Carrier Landing System with ADRC-Based Con...

引用

3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Zhu, Junfan Wang, Honglun Zhang, Menghua Ren, Bin Wu, Tiancai School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China

ISBN: (纸本)9789819710980

Aiming at the problem of carrier-based aircraft automatic carrier landing, this paper proposes a new automatic carrier landing system (ACLS) design with controller based on active disturbance rejection control (ADRC) and deck motion compensation (DMC) method with long short-term memory (LSTM) prediction. First, the six degrees of freedom nonlinear dynamic model of carrier-based aircraft and the deck motion model of aircraft carrier are established. Second, to improve the anti-disturbance performance of ACLS, the ADRC-based controller is introduced to be the inner loop controller. Third, due to the advantage in predicting long time series data, LSTM recurrent neural network is used to make prediction of deck motion and combined with the controllers of ACLS, the method of DMC is introduced. Finally, the methods proposed in this paper are verified by simulation. The simulation results show that the ADRC-based controller have better anti-disturbance performance in windy environment compared with traditional controller, and combined with DMC method, the whole system can track the motion of desired touchdown point (DTP) with the tracking error is in range of ±0.6 m. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Long short-term memory

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An innovation analysis of Machine Learning model to Automate Network Anomaly Detection through Time Series Analysis 15

An innovation analysis of Machine Learning model to Automate...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Rongali, Aruna Sri Qureshi, Anjum Nazir Upadhyay, Jyoti Lavanya, P. Matad, Nanditha S Jain, Sanjiv Kumar University of The Cumberlands Department of Information Technology United States Rajiv Gandhi College of Engineering Research and Technology Department of Electronics and Communication Chandrapur India Gd Rungta College of Science and Technology Department of Computer Science Chhattisgarh Bhilai India Institute of Aeronautical Engineering Hyderabad India New Horizon College Department of Mathematics Bangalore India Med-Caps University Department of Electrical Engineering Indore India

ISBN: (纸本)9798350370249

This paper explores the potential of machine-mastering models to automate network Anomaly Detection (NAD) through Time series analysis. We employ a two-level method wherein the primary degree entails function selection thru foremost component analysis (PCA), accompanied by gadget mastering (ML) model choice from more than a few supervised studying algorithms. The second stage evaluates the overall performance of the numerous selected ML models and optimizes theirhyperparameters when necessary. Our experiments demonstrate that ML-driven computerized network Anomaly Detection can provide accurate and well-timed detection of network anomalies with little supervision and parameter tuning attempts. The outcomes of our experiments display that Random Forests and Support Vector Machines (SVMs) carry out first-rate some of the model's grid searches, demonstrating aggressive accuracy and precision ratings from an anomaly detection perspective. We also intensely evaluate the consequences and provide insightful discussion on the possibilities and challenges surrounding using ML for automatic community Anomaly Detection. © 2024 IEEE.

关键词： Time series

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