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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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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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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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Synergy level impedance control for multifingered hands

Synergy level impedance control for multifingered hands

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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Thomas Wimböck Benjamin Jahn Gerd Hirzinger Institute of Robotics and Mechatronics German AeroSpace Center (DLR) Wessling Germany Control Engineering Group Computer Science and Automation Faculty Ilmenau University of Technology Ilmenau Germany

In many robotic manipulation tasks a robotic hand is used to just grasp and fix the object of interest while the object motion is performed by the arm. Motivated by the analysis on human grasping using data reduction techniques, we applied this concept to the DLR Hand II. Therefore, we analyzed the grasp database that was grown over the past years to find suitable robotic ¿synergy coordinates¿. 74% of these grasps can be represented by two coordinates that were originally defined by 12 joint variables. As a second step, a synergy impedance controller was derived and implemented extending the work on passivity based hand control at DLR. This controller for torque-controlled robot hands allows to imitate the behavior of a synergistic, respectively underactuated, hand. Such a controller provides furthermore a simplified interface for higher level grasping strategies and allows furthermore to manually teach new grasps easily. The controller was evaluated on the DLR Hand II by commanding steps that demonstrate the desired transient behavior. Finally, two objects were successfully grasped validating our approach.

关键词： Robot kinematics Joints Impedance Databases Grasping Symmetric matrices

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Development of Predictive Hybrid Redundancy for Fault tolerant in Safety Critical Systems

Development of Predictive Hybrid Redundancy for Fault tolera...

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International Conference on mechatronics (ICM)

作者： Byong Jum Son Ji Hoon Park Kyung Nam Ha Suk Lee Kyung Chang Lee Man Ho Kim School of Mechanical Engineering Pusan National University Busan South Korea Department of Control and Automation Engineering Pukyong National University Busan South Korea Department of Mechatronics Intelligent DGIST Daegu South Korea

As many systems depend on electronics, concern for fault tolerance is growing rapidly. For example, a car with its steering controlled by electronics and no mechanical linkage from steering wheel to front tires (steer-by-wire) should be fault tolerant because a failure can come without any warning and its effect is devastating. In order to make system fault tolerant, there has been a body of research mainly from aerospace field. This paper presents the structure of predictive hybrid redundancy that can filter out most erroneous values. In addition, several numerical simulation results are given where the predictive hybrid redundancy outperforms well-known average and median voters.

关键词： Redundancy Fault tolerant systems Hardware Fault detection Vehicle safety Electronic components Vehicle dynamics Switches Intelligent vehicles Fault tolerance

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A fuzzy track-keeping autopilot for ship steering

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Proceedings of the Institute of Marine engineering, Science and Technology Part A: Journal of Marine engineering and Technology 2003年第2期 23-29页

作者： Omerdic, E. Roberts, G.N. Vukic, Z. Mechatronics Research Centre University of Wales College Newport United Kingdom University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Department of Mechatronics United Kingdom IFAC Technical Committee on Marine Systems United Kingdom IFAC Technical Committee on Mechatronic Systems United Kingdom Department of Control Engineering University of Zagreb Faculty of Electrical Engineering and Computing Croatia IEEE Control Systems/Robotics Automation Society Croatia

In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one output (command rudder angle). The track-keeping problem is decomposed into two subtasks: (i) followthe desired heading, and (ii) bring the ship onto the desired path and keep tracking. Internally, the autopilot consists of two autopilots that fulfil these tasks simultaneously. The proposed control scheme has been verified using a non-linear model of a Mariner-class vessel and steering mechanism under the influence of wave and current disturbances. Results presented show how such a control strategy enables improved tracking performance.

关键词： Ships

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