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Multi-Objective Optimization of Electromagneticthermal Coupling Performance for High-torquedensity PMSM based on Multi-dimensional Correction Techniques

Multi-Objective Optimization of Electromagneticthermal Coupl...

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International Conference on Electrical Machines, ICEM

作者： Zequan Li Jin Wang Lu Sun Haoyu Kang Liyang Liu Libing Zhou State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Key Laboratory of Advanced Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Robotics and Autonomous Systems Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

To address the precision limitation of traditional thermal models and the computational inefficiency of electromagnetic-thermal coupling finite element models, this work proposes a multidimensional correction-based electromagnetic-thermal coupling design optimization method for electric machines. Firstly, this method corrects the sensitive parameters in the analytical lumped parameters thermal network model (LPNM) based on prior information from historical experimental data to ensure the accuracy for thermal performance analysis. Subsequently, to enhance computational efficiency, a large number of low-fidelity (LF) samples are obtained using the corrected thermal model in a serial electromagnetic-thermal field calculation manner, complemented by a small number of high-fidelity (HF) samples obtained from the electromagnetic-thermal coupling simulation model. Then, by employing a transfer learning technique, the data information from the low- to high-fidelity sample sets is comprehensively utilized to train a multi-fidelity (MF) surrogate model for the final optimization. The proposed method applied to a high-torque-density aerospace propulsion permanent magnet synchronous motor (PMSM) with short-term strong overload capability, it not only significantly improves the accuracy of LPNM, but also reduces the training sample acquisition time by over 50% under the same model accuracy. Finally, a prototype is tested to validate the effectiveness of the proposed method.

关键词： Couplings Accuracy Computational modeling Transfer learning Data models Thermal analysis Computational efficiency Iterative methods Optimization Design optimization

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The Integrated Design of Multi-Functional Metamaterial with Impact Resistance and Vibration Reduction

SSRN

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SSRN 2024年

作者： Wang, Hongyu Zhao, Jian Wang, Xuefeng Liu, Pengbo State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian China Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China

As metamaterials are widely used in engineering fields, the demand for the extraordinary properties of metamaterials is no longer satisfied with the single function. Aiming at the demand for multi-functional metamaterials with light weight, high strength, high energy absorption and vibration reduction characteristics in engineering structures, the multi-functional metamaterial integrating impact resistance and vibration reduction is proposed. In the work, a super-elastic material structure is obtained by designing curved beam in cell structure, and the impact energy is effectively limited in the rotating deformation of the structure. The overdamping effect is introduced into the design of the cell structure, and the characteristic frequency of the cell structure is changed by the strain of the tuned structure, so as to greatly improve the impact energy attenuation characteristic of the cell structure. Introducing the design concept of biomimetic metamaterials to construct lattice structures in a fractal way. The improved IHB method is introduced to analyze the bandgap properties of the lattice structure theoretically, and the filtering characteristics of large bandwidth are realized by parameter adjustment, and bandwidth range reaches 5kHz. Numerical method and finite element method were used to further verify the impact resistance and filtering performance of the structure. Through the design of multi-stage energy absorption structure, the impact resistance in the form of single-layer lattice structure was greatly improved, where impact displacement attenuation rate of more than 95% and the impact acceleration attenuation rate of more than 98%. The filter characteristics and impact resistance characteristics of the structure are verified by means of experiments. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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Reconfigurable Inflated Soft Arms

Reconfigurable Inflated Soft Arms

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IEEE International Conference on robotics and Automation (ICRA)

作者： Nam Gyun Kim Jee-Hwan Ryu Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Department of Civil and Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

Inflatable structures have attracted considerable research attention in many fields owing to their numerous advantages, such as being light and able to engage in interactions safely. However, in most cases, the inflatable structure can only have one stable configuration, which is undesirable for robotic arms. This study proposes a novel inflatable structure that can be easily reconfigured into multiple stable configurations, even with single-body inflation. In the proposed mechanism, the structure length can be freely adjusted, and its respective joints can be set in the desired directions to facilitate the reconfiguration of its pose. An additional advantage of the proposed mechanism is that it can withstand external forces as well as its own weight. This study analyzes and experimentally validates the shape locking and load-carrying properties of the proposed mechanism. Further, the fabrication process and design guidelines for the proposed mechanism are presented. Through a suitable demonstration, the proposed mechanism is shown to exhibit multiple stable configurations and lock its poses.

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Estimation of Deformation for Self-balancing Lower Limb Exoskeleton Only Using Force/Torque Sensors

Estimation of Deformation for Self-balancing Lower Limb Exos...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Chen, Ziqiang Yang, Ming Li, Feng Li, Wentao Li, Jinke Tian, Dingkui Sun, Jianquan He, Yong Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China University of Science and Technology of China Hefei230026 China China Construction Third Bureau First Engineering Mep Co. Ltd. Shenzhen518109 China

ISBN: (纸本)9798350325706

This paper presents a general estimation method of deformation for the self-balancing lower limb exoskeleton (SBLLE). In particular, we propose a Bi-LSTM deformation estimator (BLDE) to predict and compensate for the deformation of SBLLE based on the current force and torque data measured by force/torque (F/T) sensors. First, we choose four movements including squatting down and up, waist twisting, left foot lifting, and right foot lifting to mimic the constituent action of walking motion. The deformation data set is obtained through the motion capture analysis system and offline planning trajectories, and the relative F/T data set is obtained by the F/T sensors embedded in the feet of SBLLE. Second, the BiLSTM network is trained to learn the relationship between the deformation and F/T and verified on the test set. After that, BLDE is added to the control system of SBLLE to estimate and compensate for the deformation. Finally, four same movements and the walking experiment are conducted on the exoskeleton AutoLEE-G2 with BLDE. The experimental results have proven that BLDE can predict and compensate for deformation by only using F/T sensors. © 2023 IEEE.

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Enhancing Contact Stability in Admittance-Type Haptic Interaction Using Bidirectional Time-Domain Passivity Control

Enhancing Contact Stability in Admittance-Type Haptic Intera...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Seong-Su Park Huseyin Tugcan Dinc Kwang-Hyun Lee Jee-Hwan Ryu Department of Civil and Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

The present paper proposes a novel strategy to enhance admittance-type haptic interaction using bidirectional time-domain passivity control. While admittance-type haptic interaction is widely employed in human-robot collaboration, its ability to render low virtual inertia can be limited, leading to unstable interactions with rigid environments. The proposed strategy seeks to stabilize a lower range of virtual inertia while maintaining responsive behavior in free space. The Franka Emika Collaborative robot was utilized in various experiments to test the approach, and the results indicate that the bidirectional time-domain passivity controller can improve interaction performance relative to the conventional unidirectional time-domain passivity approach. This technique may aid in reducing operator fatigue during the manipulation of heavy, non-back drivable industrial robots while preserving a lightweight feel.

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engineering vascularised organoid-on-a-chip:strategies,advances and future perspectives

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Biomaterials Translational 2024年第1期5卷 21-32页

作者： Zhangjie Li Dingyuan Yu Chenyang Zhou Feifan Wang Kangyi Lu Yijun Liu Jiaqi Xu Lian Xuan Xiaolin Wang Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghaiChina National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghaiChina National Center for Translational Medicine(Shanghai)SHU Branch Shanghai UniversityShanghaiChina

In recent years,advances in microfabrication technology and tissue engineering have propelled the development of a novel drug screening and disease modelling platform known as *** platform integrates organoids and organ-on-a-chip technologies,emerging as a promising approach for in vitro modelling of human organ ***-on-a-chip devices leverage microfluidic systems to simulate the physiological microenvironment of specific organs,offering a more dynamic and flexible setting that can mimic a more comprehensive human biological ***,the lack of functional vasculature has remained a significant challenge in this *** is crucial for the long-term culture and in vitro modelling of organoids,holding important implications for drug development and personalised medical *** review provides an overview of research progress in developing vascularised organoid-on-a-chip models,addressing methods for in vitro vascularisation and advancements in vascularised *** aim is to serve as a reference for future endeavors in constructing fully functional vascularised organoid-on-a-chip platforms.

关键词： drug screening microfluidic chip organoids tissue engineering vascularisation

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Damping Injection Learning for Robots with Actor-Critic Driven by Integral Sliding Manifolds

Damping Injection Learning for Robots with Actor-Critic Driv...

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International Conference on Electrical engineering, Computing Science and Automatic Control (CCE)

作者： Alejandro Tevera-Ruiz Rodolfo Garcia-Rodriguez Vicente Parra-Vega Robotics and Advanced Manufacture-CINVESTAV Saltillo Mexico Postgraduate Program in Aerospace Engineering Univ. Politécnica Metropolitana de Hidalgo Mexico

Reinforcement Learning (RL) is characterized by enforcing a reward collection mechanism that qualifies task performance aimed at optimizing a value function that tunes the action (control). In contrast to control theory, RL satisfies two metrics simultaneously: the task metric commonly, defined as the task error, and the temporal difference (TD) error. Thus, the RL has been empowered to learn how to fulfill control tasks based on a learning stage that collects rewards that evaluate a second metric of the robot’s performance. In this way, including RL in control systems is an advantageous scheme for some critical tasks nowadays. Consequently, the stability can be guaranteed, largely missing in the RL’s literature, to safe system operation.. In this paper, we propose an Actor-Critic (AC) scheme using the Critic Neural Network (C-NN) to approximate a value function using the TD error reduction, whereas the adaptive tuning of damping injection gain is provided by the Actor NN (A-NN) to enforce stability in closed-loop finally; achieving asymptotic stability with an underlying integral sliding mode loop. In this way, our proposal contributes to a novel model-free RL scheme that yields local exponential convergence with a smooth control action. Numeric simulations for a 2-DoF robot manipulator are presented and discussed under different conditions..

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Probing Local Cellular Mechanics by Atomic Force Microscopy with Modified Spherical Tip

Probing Local Cellular Mechanics by Atomic Force Microscopy ...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Zhaofeng Zuo Xiaoming Liu Xiaoqing Tang Fengyu Liu Dan Liu Yuyang Li Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and the Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

Abstract-The mechanical characterization of cell is important for knowing the physiological state and studying diseases of organism. While many approaches are available for measuring cellular elasticity, distinguishing the stiffness variation among different cellular areas is still a challenge. In this paper, we reported a method to modify spherical atomic force microscopy (AFM) tip for accurate measurement of Young’s modulus in several areas on single adherent living cancer cells (Hela cells). The micrometer size spheres were transported to an AFM probe tip by dual micropipettes and fixed by ultraviolet (UV) curable glue, which is reproducible and nondestructive to the cantilever. The force-displacement curves were measured along major axis of cells with the modified AFM probe in indentation experiments. The results demonstrate that the modulus value increased with the detected point approaching the nucleus center, and areas closed to nucleus showed have higher stiffness. Our study provides a quantitative method for static measurement of different locations of cell, and the result has the potential to reveal how intracellular structures have effect on the cell mechanical characterization.

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A Novel Multivariate Skew-Normal Mixture Model and Its Application in Path-Planning for Very-Large-Scale Robotic Systems

A Novel Multivariate Skew-Normal Mixture Model and Its Appli...

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American Control Conference (ACC)

作者： Pingping Zhu Chang Liu Peter Estephan Faculty of Computer Sciences and Electrical Engineering Marshall University Huntington WV USA Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China Department of Computer Sciences and Electrical Engineering Marshall University Huntington WV USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper addresses the path-planning challenge for very large-scale robotic systems (VLSR) operating in complex and cluttered environments. VLSR systems consist of numerous cooperative agents or robots working together autonomously. Traditionally, many approaches for VLSR systems are developed based on Gaussian mixture models (GMMs), where the GMMs represent agents' evolving spatial distribution, serving as a macroscopic view of the system's state. However, our recent research into VLSR systems has unveiled limitations in using GMMs to represent agent distributions, especially in cluttered environments. To overcome these limitations, we propose a novel model called the skew-normal mixture model (SNMM) for representing agent distributions. Additionally, we present a parameter learning algorithm designed to estimate the SNMM's parameters using sample data. Furthermore, we develop two SNMM-based path-planning algorithms to guide VLSR systems through complex and cluttered environments. Our simulation results demonstrate the effectiveness and superiority of these algorithms compared to GMM-based pathplanning methods.

关键词： Graphical models Simulation Mixture models Control systems Robots Gaussian mixture model Distribution functions

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Eversion-Capable Fabric Robot Gripper with Novel Retraction Mechanism

Eversion-Capable Fabric Robot Gripper with Novel Retraction ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ahmed Hassan Taqi Abrar Faisal Aljaber Ivan Vitanov Kaspar Althoefer Centre for Advanced Robotics @ Queen Mary (ARQ) School of Engineering and Materials Science Queen Mary University of London London U.K.

Soft grippers have a number of advantages over their conventional stiff-bodied counterparts; not only do they surpass them in ease of fabrication and safety but also, in many cases, require less complex control strategies - due to natural compliance and form-fitting plasticity. Pneumatically actuated soft grippers made from non-extensible fabrics or polyethylene sheets have been shown to outperform soft silicone grippers capable of applying greater forces to the environment. Despite progress in the field, grasping a given object within a confined space proves challenging for both soft and conventional robotic grippers. A key issue is that most grippers use rotary or lateral translational motion when grasping an object, hence other objects in the scene may impede the closing motion as the gripper attempts to reach the target. In this study, we present a novel design for a soft robotic gripper equipped with a brace of fabric-based fingers capable, by way of eversion, of longitudinal extension, bending, and retraction, i.e. returning to a stowed state. Our experiments show that from the retracted to fully-extended state, the gripper fingers extend by up to 200% in length. To test the performance of the design, force characterisation experiments and grasping operations were carried out, demonstrating that each finger is capable of as much as 30 N of maximum tip force and can bend to an angle of 127°• At a bending pressure of 82.7 kPa (the maximum tested pressure in the bending chamber), a maximum (pullout) force of 16 N is needed to release an object that has been grasped by the finger. The experimental scenario detailed features all three mechanisms (eversion, bending and retraction) discussed.

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