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automation, control and Robots (ICACR), International Conference on

作者： Charlotte Tkany Martin Grotjahn Johannes Kühn Hochschule Hannover Institute of Engineering Design Mechatronics and Electromobility Hannover Germany RDS Motion Control Lenze Automation GmbH Braunschweig Germany

ISBN: (数字)9781728192079

ISBN: (纸本)9781728192086

Flatness-based feedforward control is an approach for combining fast motion with low oscillations for nonlinear or flexible drive systems. Its desired trajectories must be continuously differentiable to the degree of the system order. Designing such trajectories, that also reach the dynamic system limits, poses a challenge. Common solutions, like Gevrey functions, usually require lengthy offline calculations. To achieve a quicker and simpler industrial-suited solution, this paper presents a new online trajectory generation scheme. The algorithm utilizes higher order s-curve trajectories created by a cyclic filtering process using moving average filters. An experimental validation proves the capability as well as industrial applicability of the presented approach for flexible structures like stacker cranes.

关键词： Trajectory Cranes Oscillators Belts Springs Mathematical model Force

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Coordinated Operation Between Electric Vehicle Charging Stations and Distribution Power Network Considering Shared Energy and Reserve

Coordinated Operation Between Electric Vehicle Charging Stat...

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Annual Meeting Industrial and Commercial Power Systems Technical Conference

作者： Yuanzheng Li Zhixian Ni Tianyang Zhao Yun Liu Lei Wu Yong Zhao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China School of Electrical Engineering Jinan University Zhuhai China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Stevens Institute of Technology New Jersey USA

ISBN: (纸本)9781728186337

In this paper, we present a coordinated operation method for electric vehicle charging stations (EVCSs) and a distribution power network (DPN), considering integrated energy and reserve regulation. In this method, we firstly propose formulations of energy-reserve integrated decision for EVCSs with constraints of quality of service. Then, we propose a shared energy and reserve scheduling model based on the coalition game, and adopt a characteristic function to study allocations of economic benefits brought by the coordinated operation. Finally, case study verifies effectiveness of the proposed method, by investigating operation costs of EVCSs and DPN regarding the non-coordinated and coordinated modes, respectively.

关键词： Economics Quality of service Games Predictive models Regulation Electric vehicle charging Real-time systems

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An Experimental Study on Classification of Drivers Based on Confidence and Command of Driving

An Experimental Study on Classification of Drivers Based on ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Daghan Dogan Tankut Acarman Seta Bogosyan Mechatronics Engineering Dept. Istanbul Technical University Istanbul Turkey Computer Engineering Dept. Galatasaray University Istanbul Turkey Control and Automation Engineering Dept. Istanbul Technical University Istanbul Turkey

ISBN: (数字)9781728156354

ISBN: (纸本)9781728156361

This study proposes a simple classification method for drivers based on their driving confidence and authority using feedback from steering wheel angle and traction motor current measurement data. Data is collected from 38 drivers on a prototype electric vehicle. For the classification process, the driving performance of each driver is assessed with respect to an expert driver. The data is time-stamped and geo-referenced. The experimental driving data is comprised of the two command inputs that the driver generates to regulate handling and lane-level tracking. Deviations from the expert's performance data are considered to be a measure of potential failure of the driver's confidence and authority leading to a possible accident. The dataset of the participating drivers is processed by extracting the mean, standard deviation, skewness and kurtosis values. Extracted features are evaluated with different classification methods, including KNN.

关键词： Vehicles Feature extraction Hidden Markov models Torque Data collection Euclidean distance Task analysis

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Parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

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Super-k: A piecewise linear classifier based on Voronoi tessellations

arXiv

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arXiv 2020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

Voronoi tessellations are used to partition the Euclidean space into polyhedral regions, which are called Voronoi cells. Labeling the Voronoi cells with the class information, we can map any classification problem into a Voronoi tessellation. In this way, the classification problem changes into a query of just finding the enclosing Voronoi cell. In order to accomplish this task, we have developed a new algorithm which generates a labeled Voronoi tessellation that partitions the training data into polyhedral regions and obtains interclass boundaries as an indirect result. It is called Supervised k-Voxels or in short Super-k. We are introducing Super-k as a foundational new algorithm and opening the possibility of a new family of algorithms. In this paper, it is shown via comparisons on certain datasets that the Super-k algorithm has the potential of providing comparable performance of the well-known SVM family of algorithms with less complexity. Copyright © 2020, The Authors. All rights reserved.

关键词： Piecewise linear techniques

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Smooth Pick-up of Freewheeling PMSM Using EKF-Based Method for Position Sensorless control

Smooth Pick-up of Freewheeling PMSM Using EKF-Based Method f...

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automation, control and Robots (ICACR), International Conference on

作者： Nils Werner Wilcken Martin Grotjahn Thomas Eutebach Institute of Engineering Design Mechatronics and Electromobility (IKME) University of Applied Sciences and Arts Hannover Germany RDS Motion Control Lenze Automation GmbH Aerzen Germany

ISBN: (数字)9781728192079

ISBN: (纸本)9781728192086

In this paper, a new extended Kalman filter (EK) based rotor position observer for permanent magnet synchronous machines (PMSM) is presented. With this method, just one single EKF is sufficent to evaluate the position information from EMF and anisotropy. Thus, PMSM can be controlled in the entire speed range without a position sensor and without the need to switch or synchronize between different observers. Furthermore, the phase delay in the feedback path of the control loop is reduced. With the increased accuracy of the estimated rotor position and speed, the resulting control behavior is optimized. This makes a smooth pick-up of freewheeling PMSM possibly, even if starting conditions are unknown. Demonstrated by measurements, the position sensorless control behavior shows an optimized dynamic.

关键词： Rotors Observers Mathematical model Current measurement Anisotropic magnetoresistance Switches Synchronization

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Experimental Prototype of High-Efficiency Wind Turbine Based on Magnus Effect

Experimental Prototype of High-Efficiency Wind Turbine Based...

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International Workshop on Electric Drives: Optimization in control of Electric Drives (IWED)

作者： Aleksandr Lukin Galina L. Demidova Dmitry V. Lukichev Anton Rassõlkin Ants Kallaste Toomas Vaimann Anouar Belahcen Faculty of Control System and Robotics ITMO University Saint Petersburg Russia Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallin Estonia Department of Electrical Engineering and Automation Aalto University Helsinki Finland

ISBN: (数字)9781728141589

ISBN: (纸本)9781728141596

The main feature of Magnus wind turbine is the ability to produce energy at low wind speed. This benefit lets to use such types of turbines in smart homes, which are an important part of the development of distributed energy systems, growth of blockchain electricity technology and needs for duplication of the solar energy system in the private buildings. This paper presents topology of two cylinders Magnus wind turbine in order to ensure the highest values of power coefficient and the Magnus force. The optimal ratio of wind speed and cylinder rotation speed were detected to eliminate the oscillations caused by the Von Karman vortex street phenomenon.

关键词： Wind turbines Force Drag Rotors Mathematical model Wind speed Generators

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Magnus Wind Turbine: Finite Element Analysis and control System

Magnus Wind Turbine: Finite Element Analysis and Control Sys...

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International Symposium on Power Electronics, Electrical Drives, automation and Motion, SPEEDAM

作者： Galina L. Demidova Alecksey Anuchin Aleksandr Lukin Dmitry Lukichev Anton Rassõlkin Anouar Belahcen Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia Department of Electrical Engineering and Automation Aalto University Helsinki Finland

ISBN: (数字)9781728170190

ISBN: (纸本)9781728170206

Due to its special features, the Magnus effect wind turbine allows you to produce energy at a very low speed of the wind. This fact, as well as the growing interest in the of blockchain technology, makes it possible to use this type of wind turbine in private household as part of a distributed energy system in addition to solar panels. The article describes a two blades Magnus wind turbine whose cylinders rotate by means of embedded motors. To avoid a von Karman vortex street effect that occur when the cylinders rotate in the air flow, as well as to ensure maximum power, the optimal ratio between the wind speed and the cylinder rotation speed is determined using finite element analysis. Further, the obtained relations are used in the algorithms of the wind turbine control system.

关键词： Wind turbines Force Wind speed Generators Mathematical model Torque control systems

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Motion Planning and control with Randomized Payloads on Real Robot Using Deep Reinforcement Learning

Motion Planning and Control with Randomized Payloads on Real...

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作者： Demir, Ali Sezer, Volkan Mechatronics Engineering Istanbul Technical University Maslak Istanbul34496 Turkey TOFAŞ Turkish Automobile Company RandD Center Bursa Turkey Control and Automation Engineering Istanbul Technical University Maslak Istanbul34496 Turkey

In this study, a unified motion planner with low level controller for continuous control of a differential drive mobile robot under variable payload values is presented. The deep reinforcement agent takes 11-dimensional state vector as input and calculates each wheel's torque value as a 2-dimensional output vector. These torque values are fed into the dynamic model of the robot, and lastly steering commands are gathered. In previous studies, intersection navigation solutions that uses deep-RL methods, have not been considered with variable payloads. This study is focused specifically on service robotic applications where payload is subject to change. In this study, deep-RL-based motion planning is performed by considering both kinematic and dynamic constraints. According to the simulations in a dynamic environment, the agent successfully navigates to target with 98.2% success rate in test time with unseen payload masses during training. Another agent is also trained without payload randomization for comparison. Results show that our agent outperforms the other agent, that is not aware of its own payload, with more than 40% gap. Our agent is also compared with the Time-to-Collision (TTC) algorithm. It is observed that our agent uses far less time than TTC to accomplish the mission while success rates of two methods are same. Lastly, the proposed method is applied on a real robot in order to show the real-time applicability of the approach. © 2019 World Scientific Publishing Company.

关键词： Reinforcement learning

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Evacuation control of Crowds of Pedestrians: Distributed or Decentralized? ⁎

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IFAC-PapersOnLine 2020年第5期53卷 318-323页

作者： Kecai Cao YangQuan Chen Chenglin Liu Nanjing Institute of Technology Nanjing 211167 China Mechatronics Embedded Systems and Automation Lab School of Engineering University of California Merced CA USA 95343 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 China

Evacuation of crowds in a corridor with only one exit has been considered in this paper where distributed controllers have been constructed to regulate the crowd’s evacuation speed so that stampede tragedy can be avoided. Macroscopic model for crowds of pedestrians has been firstly derived based on inspiration of LWR (Lighthill-Whitham and Richards) model and Greenshields model from traffic system where finite volume method has been introduced to simplify the obtained PDEs into finite ODEs. Distributed evacuation controllers have been constructed based on inspiration of multi-agent system and stability analysis of obtained closed-loop system has been simplified to linear system with the delicate controllers proposed. Comparisons between distributed evacuation controllers and previous evacuation controllers have also been presented to show the advantages and disadvantages of different controllers under different initial density of crowds so that tragedy of crowd stampede can be effectively avoided with appropriate selection of different controllers.

关键词： Distributed evacuation controller Decentralized evacuation controller Stampede

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