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arXiv 2022年

作者： Zengin, Rahman Salim Sezer, Volkan Department of Mechatronics Engineering Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey Autonomous Mobility Group Electrical and Electronics Engineering Faculty Istanbul Technical University Istanbul Turkey

Training of a Machine Learning model requires sufficient data. The sufficiency of the data is not always about the quantity, but about the relevancy and reduced redundancy. Data-generating processes create massive amounts of data. When used raw, such big data is causing much computational resource utilization. Instead of using the raw data, a proper Condensed Representation can be used instead. Combining K-means, a well-known clustering method, with some correction and refinement facilities a novel Condensed Representation method for Machine Learning applications is introduced. To present the novel method meaningfully and visually, synthetically generated data is employed. It has been shown that by using the condensed representation, instead of the raw data, acceptably accurate model training is possible. Copyright © 2022, The Authors. All rights reserved.

关键词： K-means clustering

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Design of A Novel Primary Permanent Magnet Linear Machine with Low Thrust Ripple

Design of A Novel Primary Permanent Magnet Linear Machine wi...

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IEEE Student Conference on Electric Machines and Systems

作者： Jiawei Chai Jiajia Xu Xianguo Gui Qiang Gao School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China Innovation Center for Control Actuators Beijing Institute of Precision Mechatronics and Controls Beijing China

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

In order to reduce thrust ripple, this paper proposes a new primary permanent magnet linear machine with uneven pole (UP-PPMLM). Firstly, the proposed structure and advantages compared to conventional structure are introduced. Then, the expressions of air-gap flux density by permanent magnets (PMs) and armature reaction are derived. Finally, by using finite element method (FEM), the new topology reasonability is proved. Meanwhile, the performances of proposed machines are compared to conventional topology, and the result confirms the electromagnetic performances of the proposed machine have been greatly improved.

关键词： Electric machines Air gaps Force Modulation Armature Permanent magnets Finite element analysis Topology Electromagnetics Optimization

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Development of fuzzy logic water bath temperature controller using MATLAB

Development of fuzzy logic water bath temperature controller...

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2012 IEEE International Conference on control System, Computing and engineering, ICCSCE 2012

作者： Hasim, Norhaslinda Aras, Mohd Shahrieel Mohd Rashid, Mohd Zamzuri Ab Kassim, Anuar Mohamed Abdullah, Shahrum Shah Department of Control and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Mechatronics Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Department of Electric and Electronics Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia

ISBN: (纸本)9781467331432

In this paper, the development of a water bath temperature system to control the liquid's temperature in the water bath will be presented. In order to develop the water bath temperature control system, MATLAB fuzzy logic toolbox will be utilized. The Fuzzy Logic controller (FLC) is designed to control water temperature based on the input acquired from the thermal transducer sensor. The inference engines that are used are;Max-min (Mamdani) method and centre of gravity technique for defuzzification. The 4 × 4 matrix rules for the controller will be used in this project. In addition, the USB NI-DAQ card will be used as xPC target to link the MATLAB software and real time application. The real time output temperature is validated based on the simulation's temperature which is initially set by user. It can be concluded the performance of real time study is in par with the simulation result. © 2012 IEEE.

关键词： MATLAB

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Application of optimization technique for PID controller tuning in position tracking of pneumatic actuator system

Application of optimization technique for PID controller tun...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： N.H Sunar M.F. Rahmat Z. H. Ismail A. M. Faudzi Sy Najib Sy Salim Sharatul Izah Samsudin Department of Mechatronics and Control Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Control Instrument and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Department of Industrial Electronics Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

In this paper, two optimization techniques of Particle Swarm Optimization (PSO) and Firefly Algorithm (FA) is used to obtain the optimal PID control parameters. To represent the model of the system, system identification with ARX model structure is developed. The results are determined by analysis the step response characteristic of the system. It was observed that the performances of PID controller with PSO optimized parameters perform well in position tracking of the pneumatic actuator system.

关键词： Tuning Zinc Optimization Signal processing algorithms PD control Pneumatic actuators

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Autonomous Servo-Electro Braking System for High-Speed EV

Autonomous Servo-Electro Braking System for High-Speed EV

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International Conference on mechatronics (ICOM)

作者： Rahman Md Ataur M Habibullah Sany Ihsan Mahbubur Rashid Salmiah Ahmed GameAbove Engineering and Technology Eastern Michigan University Ypsilanti Michigan USA Mechanical and Aerospace Engineering Kulliyyah of Engineering International Islamic University Malaysia Mechatronics Engineering Kulliyyah of Engineering International Islamic University Malaysia Automation and Control System Engineering College of Engineering and Technology University of Doha for Science and Technology Doha Qatar

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Rising in popularity of electric vehicles on the roads has created several challenges. Accidents remain one of the most serious road accidents due to which the high-voltage batteries in electric vehicles can lead to fire or even instant death of the passenger(s). Autonomous Emergency Braking System (AEBS) was developed to solve braking problems associated with ABS. However, the system is designed to notify the driver rather than act on it, so there is always a high chance that AEBS continually causes problems when driving in close proximity. In addition, AEBS is only intended for vehicles with low speeds of around 70 km/h. The purpose of this paper is to present the development of a fuzzy intelligent adaptive autonomous servo-electromagnetic braking system (ASEBS) for both close-range driving and high-speed electric vehicles to avoid or mitigate a collision without driver reaction. An intelligent fuzzy logic algorithm was introduced to automatically brake the vehicle regardless of its operating speed and vehicle-to-object (V20) distance to prevent or mitigate a collision. An intelligent fuzzy logic controller controls the power flow to the servo-electromagnetic drive to provide vehicle deceleration and emergency stop. A laboratory pilot model of ASEBS with a double drive has been developed. The ASEBS intelligent fuzzy logic controller has been tested under uniform deceleration and emergency braking of a vehicle, both when driving in close proximity and high speed.

关键词： Fuzzy logic Road accidents mechatronics Roads Prevention and mitigation High-voltage techniques Electric vehicles

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Development of an Adaptive Technology for Distance Learning of Microprocessor Technology Based on Immunological Homeostasis

Development of an Adaptive Technology for Distance Learning ...

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2023 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2023

作者： Samigulina, Galina Samigulina, Zarina Porubov, Dmitriy Institute of Information and Computing Technologies Lab. Intellectual Control Systems and Forecasting Almaty Kazakhstan Kazakh - British Technical University School of Information Technologies and Engineering Almaty Kazakhstan East Kazakhstan Technical University Named after D. Serikbayev Competence and Technology Transfer Center in the Field of Automation and Mechatronics Ust-Kamenogorsk Kazakhstan

ISBN: (纸本)9781665475952

At present, with the development of modern IT technologies and artificial intelligence methods, it is relevant to develop adaptive distance education systems for students of technical specialties capable of providing a personalized cognitive approach to the process of obtaining knowledge and timely adjustment of the learning trajectory. Particular difficulties arise when teaching the principles of operation of complex industrial equipment based on microprocessor technology, the basics of programming and the development of automatic control systems based on them. The problems associated with the complexity of adapting technical training courses for specific students and the peculiarities of information perception in the absence of direct contact with the teacher can be successfully solved with the introduction of algorithms based on a unified artificial immune system (UAIS). An innovative e-learning technology is proposed for students of engineering specialties in order to obtain high-quality technical professional education in a short time on real industrial equipment. When creating the technology and predicting the learning outcomes of students, immunological homeostasis was used to quickly correct the learning process. UAIS was developed on the basis of modified clonal selection, negative selection and immune network algorithms in order to identify the most effective of them in predicting multivariate dynamic data about students and forming an adequate immune response to maintain immunological homeostasis. The main stages and advantages of the proposed technology are given. The simulation results were obtained with the participation of students of the Faculty of Information Technology on the basis of the Kazakh-British Technical University. © 2023 IEEE.

关键词： engineering education

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Friction feedforward compensation and position feedforward in CNC machines

Friction feedforward compensation and position feedforward i...

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7th Annual International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2010

作者： Suteeratanapirom, Wijin Rattanawaorahirankul, Rapeepong Laosapan, Chutima Sanposh, Peerayot Chayopitak, Nattapon Tungpimolrut, Kanokvate Kunieda, Hiroaki TAIST Tokyo Tech ICTES Program Department of Electrical Engineering Kasetsart University 50 Phahonyothin Rd. Ladyao Jatujak Bangkok 10903 Thailand Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University 50 Phahonyothin Rd. Ladyao Jatujak Bangkok 10903 Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center 112 Thailand Science Park Phahonyothin Rd. Klong 1 Klong Luang Pathumthani 12120 Thailand Department of Electrical and Electronic Engineering Tokyo Institute of Technology S3-65 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan

ISBN: (纸本)9789746724913

This research proposes a method to eliminate friction effect and reduced tracking error on CNC milling machines. A CNC milling machine has many connected mechanical components which have friction effects such as ball screws and rails. To control servo motors which are used to drive X-Y table in CNC milling machine, the conventional PID controller is widely used. In this research, Panasonic motor driver is set to the torque control mode. To compensate the friction effects, the friction feedforward compensation method is proposed. Moreover, to reduce the position tracking error, position feedforward controller is used. The simulation and implementation of position control in one axis of PID with Friction Feedforward Compensation and Position Feedforward controller (FFC-PFC) are presented.

关键词： Friction

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Parameter identification of a Linear Permanent Magnet motor using Particle Swarm Optimization

Parameter identification of a Linear Permanent Magnet motor ...

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International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Tithiwat Therdbankerd Peerayot Sanposh Nattapon Chayopitak Hideaki Fujita Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University Bangkok Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center Klong Luang Pathum Thani Thailand Department of Electrical and Electronic Engineering Tokyo Institute of Technology Meguro Tokyo Japan

ISBN: (纸本)9781424456062;9789746724913

Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.

关键词： Parameter estimation Permanent magnet motors Particle swarm optimization Synchronous motors Signal processing Robotics and automation Chirp Intelligent robots control systems Laboratories

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Online Volt-Var control Based on Reinforcement Learning in Active Distribution Systems Considering PV Inverters

Online Volt-Var Control Based on Reinforcement Learning in A...

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International Conference on Power and Energy Technology (ICPET)

作者： Changlei Gu Xian Zhang Hong Wang Ahmed Rabee Sayed Guibin Wang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Electric Power Research Institute China Southern Grid Guangzhou China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

Due to the wide deployment of photovoltaic (PV) power generation, voltage stability is facing a severe challenge in the active distribution networks (ADNs). Reinforcement Learning (RL) techniques have been widely adopted in the power system optimal operation and quick control with high-performance achievements. Existing RL algorithms can handle only homogenous control action spaces, i.e., either continuous or discrete actions. However, the voltage control problem has hybrid action spaces. This paper proposes a hybrid soft actor-critic (H-SAC) algorithm for online quick-optimal voltage control. First, the problem is formulated to consider all types of control actions, including the setpoints of PV inverters. Second, it is standardized to be compatible with RL techniques. Third, the fundamental sample-efficient entropy-based maximization SAC algorithm is enhanced to train a policy with hybrid action spaces, where an action selection method is employed to map the continuous output of the actor-network into the integer action spaces. The proposed method is applied to the modified IEEE 33-bus system, where the voltage has been controlled with a very low computational burden.

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Performance of Virtual Stimulus Motion based on the SSVEP-BCI

Performance of Virtual Stimulus Motion based on the SSVEP-BC...

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International Symposium on Computer, Consumer and control

作者： Nannan Zhang Yang Yu Erwei Yin Zongtan Zhou Department of Automatic Control College of Mechatronics and Automation National University of Defense Technology National Key Laboratory of Human Factors Engineering China Astronaut Research and Training Center

ISBN: (纸本)9781509030729

In this paper, a brain-computer interface (BCI) paradigm based on steady-state visually evoked potentials (SSVEP) is used to determine the motion effects of stimulus targets on the classification accuracy and signal-to-noise ratio (SNR) in a virtual environment. Several paths including fixed and up/down with different speeds were set to look for performance differences. Experimental results show that the accuracy with moving targets is sometimes better than that for conventional non-moving targets, and even the relative SNR is improved with motion on occasions. This provides a basis for intensive study of the influence of moving objects on BCIs and target detection in real environments.

关键词： BCI SSVEP Stimulus motion

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