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17th IEEE International Conference on mechatronics and automation, ICMA 2020

作者： Duan, Xiaoshuai Zhang, Xinhua Huo, Xijian Li, Xiaobin Hao, Minghui Beijing Institute of Automation and Control Equipment Beijing China Harbin Institute of Technology School of Mechatronics Engineering Harbin Heilongjiang Province China

ISBN: (纸本)9781728164151

Aiming at the problem of the thread processing process of the planetary roller screw mechanism (PRSM), the theory, simulations and experiments of the thread turning are studied in this paper. Firstly, the unit cutter model and the main cutting force model of thread turning of PRSM are established based on the minimum energy method. And the finite element simulations calculation of thread turning of PRSM are performed, which analyze the influence of cutting parameters (cut depth, speed of cutting and the lathe) on the cutting force, the cutting temperature and the tool wear. Finally, the turning experiments of the screw rod are performed. The results show that the finite element simulations can effectively ensure thread processing process PRSM. © 2020 IEEE.

关键词： Screws

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A Frequency Up-Conversion Rotational Energy Harvester with Auxetic Structures for High Power Output

SSRN

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SSRN 2022年

作者： Chen, Keyu Fang, Shitong Lai, Zhihui Liao, Wei-Hsin Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong Institute of Intelligent Design and Manufacturing The Chinese University of Hong Kong Shatin Hong Kong College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China

Rotational energy harvesters (REH) have been explored to substitute conventional batteries for small electronic sensors. However, there still exists a challenge for rotational energy harvesters to scavenge sufficient energy under low-rotational-frequency excitations. In this paper, we propose a plucking rotational energy harvester with auxetic structures, which utilizes the frequency up-conversion and auxetic structures to enhance the power output of the rotational energy harvesting under low-rotationalfrequency excitations. Finite element simulation is performed to analyze the performance of the proposed rotational energy harvester. The simulation results match well with the experimental ones. When the magnet distance is set to be 2.5 mm, the maximum power output of the auxetic plucking rotational energy harvester (APREH) is found to be 1.43 mW at 1.1 Hz, which is increased by 686% compared with the conventional plain plucking rotational energy harvester (PPREH). In addition, compared with typical plucking rotational energy harvesters, the proposed auxetic plucking rotational energy harvester achieves the highest power output under low-rotational-frequency excitations, which validates the advantage of adopting auxetic structures in plucking rotational energy harvesters. © 2022, The Authors. All rights reserved.

关键词： Energy harvesting

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Air-ground cooperative exploration of 3D complex environment with maximized visibility and obstacles avoidance

Air-ground cooperative exploration of 3D complex environment...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Wu, YuXuan Wang, Jing Zhou, Meng Dong, Zhe Chen, YangQuan College of Information Science and Technology Beijing University of Chemical Technology Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China Mechatronics Embedded Systems and Automation Lab University of California MercedCA95343 United States

ISBN: (纸本)9780738131153

Unmanned aerial vehicles (UAVs) can provide vision at high altitude. In this paper, multi-UAVs and ground vehicle are utilized to explore a complex environment with obstacles. The desired UAV formation is proposed around ground vehicle to provide wider vision. The Interfered Fluid Dynamical System (IFDS) method is utilized to guide UAVs avoid obstacles, while the desired formation need be maintained. Then formation control scheme of multi-UAVs is updated to combine with IFDS method according to original formation and obstacles avoidance. Simulation results shows that multi-UAVs can avoid obstacles and maintain the desired formation around ground vehicle during exploration. © 2021 IEEE.

关键词： Ground vehicles

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Data-Driven control and Behavior-Based control Applied to a SISO Mobile Robot

Data-Driven Control and Behavior-Based Control Applied to a ...

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IEEE Latin American Robotics Symposium, LARS

作者： M. A. Pastrana Karine R. Santos Alceu B. C. de Farias Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Faculty of Gama Biomedical Engineering Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

With the advancement of technology, systems in many different areas of application have become more complex, and obtaining reliable mathematical models is a task that is increasingly becoming more difficult as well. To overcome these issues, new methodologies have emerged, such as the one known as Data-Driven-control (DDC), which uses the input and output data of the system to design a controller, and Behavior-Based-control (BBC), which provides the controller based on the desired behavior of a system. In this work, these two methodologies were applied to obtain the transfer function of a Single-Input Single-Output mobile robotic platform that moves parallel to a wall. A Proportional Integral Derivative controller was used to control the left wheel, while the right wheel was set to a constant speed, allowing the mobile robot to maintain a constant distance from the wall. The controller was tuned utilizing root locus methodology with an overshot of 16.7%, settling time of 6.45 seconds, and a static error of 2.1%. Additionally, disturbances were added to test the robustness of the mobile robot model and the PID controller.

关键词： Analytical models Biological system modeling Wheels Transfer functions Robot sensing systems control systems Mathematical models

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EXAMINATION OF WATERPROOF POCKETS AS PROTECTIVE CARRIERS FOR SMART GARMENTS

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Tekstil ve Muhendis 2022年第126期29卷 80-87页

作者： Akkan, Taner Kara, Şükran Ağin, Berk Yeşİlpinar, Sevil Şenol, Yavuz Dokuz Eylul University Izmir Vocational School Department of Mechatronics Izmir Turkey Dokuz Eylul University Faculty of Engineering Department of Textile Eng. Izmir Turkey İstanbul Technical University Control & Automation Engineering Dept. İstanbul Turkey Dokuz Eylul University Faculty of Engineering Electrical and Electronics Eng. Dept. Izmir Turkey

The importance of smart garments is increasing day by day for entertainment, sports, medical and military fields. Both hard electronics and textile based soft electronics find application in these areas. In our previous study, we focused on crew loss detection system that was applicable for team sports such as sailing. We designed a two pieces electronic system in which a master system was fixed on the boat and a slave system was implemented in the sailing garments. This study brought a new requirement;the need of a waterproof case that would protect the electronic slave system from sea water in case the sailors fall overboard. As a result of this need, in this study, we have designed and tested waterproof pockets that could serve as waterproof carriers for the slave system of sailing garments. For this purpose, studies were carried out using two different approaches. In the first approach, 15 types of pockets were developed by using three different fabric materials and 5 different seam sealing techniques. These pocket prototypes were tested by exposing them to the water for 12 h. In the second approach, an electronic circuit was developed by using a humidity sensor to test the pocket samples those were immersed to water. According to the results of the first approach, samples containing polyester base fabric, polyurethane and polyester membrane and double-sided sealing tape gave the best results. By converting the best pocket design into a garment sleeve, the humidity sensor containing test apparatus was tested and measurements were taken successfully from the system © 2022. Tekstil ve *** Rights Reserved

关键词： Humidity sensors

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Stability investigation and control synthesis of RLC ladder circuits modeled as uncertain spatially interconnected systems*

Stability investigation and control synthesis of RLC ladder ...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Dongdong Zhao Li Xu Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland School of Information Science and Engineering Lanzhou University Lanzhou China Department of Intelligent Mechatronics Akita Prefectural University Akita Japan

ISBN: (纸本)9781665476881

This paper deals with the problem of stability analysis and control scheme synthesis for RLC ladder circuits modeled as two-dimensional $(2D)$ systems, to which class spatially interconnected systems can be associated. This is because in the state-space model more than one indeterminates appear (time - continuous and the coordinates of the node in the structure - discrete). Hence analysis and control synthesis of such systems require developing new results from the systems theory area. As discussed later on due to the finite number of nodes in real systems under consideration, one option (exploited in this paper) for the analysis and synthesis of such systems is embedding temporal and spatial (node to node) dynamics into one 1D, i.e. $n=1$ , model. In this paper, RLC circuits, displayed as a series, i.e. along one spatial (node) indeterminate, constructed with conductances (resistors - R), inductances (L) and capacitors (C), considered are built of electronic elements with values given with some tolerance. This motivates the application of uncertain state-space model with the polytopic type of uncertainty. Then, for such a model, the Linear Matrix Inequalities (LMI) based methodology towards stability analysis and controller design methodology are developed. It actually leads to interesting results from the robust control area. The case study proves the correctness of the proposed methods.

关键词： Analytical models Uncertainty Two dimensional displays RLC circuits Interconnected systems Stability analysis State-space methods

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Energy Optimization of Wind Turbines via a Neural control Policy Based on Reinforcement Learning Markov Chain Monte Carlo Algorithm

arXiv

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arXiv 2022年

作者： Aghaei, Vahid Tavakol Agababaoglu, Arda Bawo, Biram Naseradinmousavi, Peiman Yıldırım, Sinan Yeşilyurt, Serhat Onat, Ahmet Istinye University Faculty of Engineering and Natural Sciences Electrical and Electronics Engineering Istanbul Turkey Sabanci University Orhanli Tuzla Istanbul34956 Turkey Delivers AI ITU Arı Technological Park Istanbul Turkey Sabanci University Faculty of Engineering and Natural Sciences Mechatronics Engineering Istanbul Turkey San Diego State University Dynamic Systems and Control Laboratory San Diego United States Sabanci University Faculty of Engineering and Natural Sciences Industrial Engineering Istanbul Turkey Istanbul Technical University Control and Automation Engineering Istanbul Turkey

This study focuses on the numerical analysis and optimal control of vertical-axis wind turbines (VAWT) using Bayesian reinforcement learning (RL). We specifically address small-scale wind turbines, which are well-suited to local and compact production of electrical energy on a small scale, such as urban and rural infrastructure installations. Existing literature concentrates on large scale wind turbines which run in unobstructed, mostly constant wind profiles. However urban installations generally must cope with rapidly changing wind patterns. To bridge this gap, we formulate and implement an RL strategy using the Markov chain Monte Carlo (MCMC) algorithm to optimize the long-term energy output of a wind turbine. Our MCMC-based RL algorithm is a model-free and gradient-free algorithm, in which the designer does not have to know the precise dynamics of the plant and its uncertainties. Our method addresses the uncertainties by using a multiplicative reward structure, in contrast with additive reward used in conventional RL approaches. We have shown numerically that the method specifically overcomes the shortcomings typically associated with conventional solutions, including, but not limited to, component aging, modeling errors, and inaccuracies in the estimation of wind speed patterns. Our results show that the proposed method is especially successful in capturing power from wind transients;by modulating the generator load and hence the rotor torque load, so that the rotor tip speed quickly reaches the optimum value for the anticipated wind speed. This ratio of rotor tip speed to wind speed is known to be critical in wind power applications. The wind to load energy efficiency of the proposed method was shown to be superior to two other methods;the classical maximum power point tracking method and a generator controlled by deep deterministic policy gradient (DDPG) method. © 2022, CC BY-NC-ND.

关键词： Reinforcement learning

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Optimal Tracking control of Injection Speed in Injection Molding Machine with Gaussian Process Learning and Model Predictive control

Optimal Tracking Control of Injection Speed in Injection Mol...

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第43届中国控制会议

作者： Jianpu Cai Zhigang Ren Bo Zhang Zongze Wu School of Automation Guangdong Key Laboratory of IoT Information Technology Guangdong University of Technology Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing (GDUT) Ministry of Education College of Mechatronics and Control Engineering Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)Shenzhen University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Injection molding, as a common plastic processing technology, has significant importance in modern manufacturing industry. However, due to the nonlinear dynamic characteristics of injection molding machines(IMMs) and the influence of various factors such as raw materials, equipment, and environment during the injection molding process(IMP), uncertainty residuals are generated, which makes it difficult to achieve optimal tracking control of injection speed, thereby affecting product quality and production efficiency. To address this issue, we propose a learning-based model predictive control(LMPC) *** scheme uses Gaussian process regression(GPR) to predict and model uncertainty residuals in the IMP. The residual model of IMM is learned through historical injection molding data, and the model predictive control(MPC) is used to achieve optimal tracking control of injection speed based on the predicted model, thereby automatically adjusting the injection speed according to requirements. In addition, we use differential dynamic programming with control constraints to solve the optimization ***, we conduct comprehensive numerical simulation experiments to prove the effectiveness and efficiency of the proposed LMPC scheme in injection speed control of IMM.

关键词： Injection molding model predictive control optimal control gaussian process learning control

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Cascaded Model Predictive control of Underactuated Bipedal Walking with Impact and Friction Considerations

Cascaded Model Predictive Control of Underactuated Bipedal W...

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IEEE-RAS International Conference on Humanoid Robots

作者： Sait Sovukluk Christian Ott M. Mert Ankaralı Automation and Control Institute (ACIN) TU Wien Vienna Austria Department of Electrical and Electronics Engineering Middle East Technical University (METU) Ankara Turkey Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany METU Robotics and AI Technologies Application and Research Center (METU-ROMER) Ankara Turkey

This study demonstrates a cascaded model predictive control (C-MPC) method for input constrained control of underactuated planar bipedal walking with any predefined sta-bilizable trajectory. Our approach aims to increase the trajectory tracking performance of the system and produce realistic and applicable responses while respecting friction constraints and considering impact dynamics. Primarily focusing on zero dynamics with PD (ZD+PD) control, this proposed control method constitutes a second layer controller on top of the well-known trajectory tracking controllers for underactuated bipedal walking systems. We successfully implement this model-based controller and test against large modeling errors, noises, and disturbances, where the conventional ZD+PD control fails to maintain stability.

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Experimental Prototype of High-Efficiency Wind Turbine Based on Magnus Effect 27

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

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27th International Workshop on Electric Drives: MPEI Department of Electric Drives 90th Anniversary, IWED 2020

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

ISBN: (纸本)9781728141589

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. © 2020 IEEE.

关键词： Wind power

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