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Simulation of magnetization process and Faraday effect of magnetic bilayer films

Chinese Physics B 2024年第9期33卷 590-597页

作者： Sheng Gao An Du Lei Zhang Tian-Guang Li Da-Cheng Ma Department of Basic and General Studies Shenyang Institute of Science and TechnologyShenyang 110167China College of Science Northeastern UniversityShenyang 110819China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Office of Academic Research Shenyang Institute of Science and TechnologyShenyang 110167China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy ofSciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110016China

We described ferromagnetic film and bilayer films composed of two ferromagnetic layers coupled through antiferromagnetic interfacial interaction by classical Heisenberg model and simulated their magnetization state,magnetic permeability,and Faraday effect at zero and finite temperature by using the Landau–Lifshitz–Gilbert(LLG)*** results indicate that in a microwave field with positive circular polarization,the ferromagnetic film has one resonance peak while the bilayer film has two resonance ***,the resonance peak disappears in ferromagnetic film,and only one resonance peak emerges in bilayer film in the negative circularly polarized microwave *** the microwave field’s frequency exceeds the film’s resonance frequency,the Faraday rotation angle of the ferromagnetic film is the greatest,and it decreases when the thickness of the two halves of the bilayer is *** the microwave field’s frequency remains constant,the Faraday rotation angle fluctuates with temperature in the same manner as spontaneous magnetization *** a DC magnetic field is applied in the direction of the anisotropic axis of the film,the Faraday rotation angle varies with the DC magnetic field and shows a similar shape of the hysteresis loop.

关键词： magnetic bilayer films magnetic permeability hysteresis loop Faraday effect Landau-Lifshitz-Gilbert(LLG)equation

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Three-Dimensional Optimal Trajectory Tracking Control of Underactuated Autonomous Underwater Vehicles Using Double Closed-Loop Control 5

Three-Dimensional Optimal Trajectory Tracking Control of Und...

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5th International Conference on intelligent Autonomous Systems, ICoIAS 2022

作者： Gong, Huibin Joo, Meng Liu, Tianhe Zhao, Xudong Institute of Artificial Intelligence and Marine Robotics College of Marine Electrical Engineering Dalian Maritime University Dalian China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

In this paper, a double closed-loop control method is proposed for three-dimensional optimal trajectory tracking control of underactuated autonomous underwater vehicles (AUVs), Firstly, a five-degree-of-freedom mathematical model of under-Actuated AUV is established. Secondly, an output redefinition method is adopted to solve underactuated control problem. On this basis, a backstepping method is utilized to design the outer-loop controller where virtual velocity is derived using the error between input and output of the system. Next, an adaptive dynamic programming method is used to design the inner-loop controller, where the performance index function containing the disturbance upper bound is set, and a neural network is employed to solve the Hamilton-Jacobi-Bellman equation online. Finally, the Lyapunov theorem is used to establish that all signals of the closed-loop system are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed method. © 2022 IEEE.

关键词： Autonomous underwater vehicles

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Feature Enhancement and Reweighting for Transformer-Based Change Detection

Feature Enhancement and Reweighting for Transformer-Based Ch...

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2022 Chinese Automation Congress, CAC 2022

作者： Shao, Sicheng Lu, Zheng Zhang, Bin Zhang, Xuetao Xi'An Jiaotong University Institute of Artificial Intelligence and Robotics Xi'an710049 China China Academy of Space Technology Institute of Remote Sensing Satellite China Xi'An Jiaotong University Zhengzhou Key Laboratory of Intelligent Assembly Manufacturing and Logistics Optimization School of Software China

ISBN: (纸本)9781665465335

As Transformer is more widely used in the domain of Computer Vision (CV), modern techniques for Change Detection (CD) have also begun to use Transformer structures, including Bitemporal Image Transformer (BIT). Although BIT shows excellent performance due to its efficient context modeling ability, the simple backbone network and the Cross-Entropy (CE) loss it uses still have room for improvement. In this paper, we propose a Feature Pyramid Network of Change Detection (FPN-CD) and a Change Detection focal (CDF) loss to address the shortcomings of the BIT method. Meanwhile, the outcomes of ablation experiments performed on two CD datasets attest to the method's efficacy. © 2022 IEEE.

关键词： Change detection

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Start State Selection for Control Policy Learning from Optimal Trajectories

Start State Selection for Control Policy Learning from Optim...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Christoph Zelch Jan Peters Oskar von Stryk Department of Computer Science TU Darmstadt Simulation Systems Optimization and Robotics Group Darmstadt Germany Department of Computer Science Intelligent Autonomous Systems Group TU Darmstadt Darmstadt Germany

Combination of optimal control methods and machine learning approaches allows to profit from complementary benefits of each field in control of robotic systems. Data from optimal trajectories provides valuable information that can be used to learn a near-optimal state-dependent feedback control policy. To obtain high-quality learning data, careful selection of optimal trajectories, determined by a set of start states, is essential to achieve a good learning performance. In this paper, we extend previous work with new comple-menting strategies to generate start points. These methods complement the existing approach, as they introduce new criteria to identify relevant regions in joint state space that need coverage by new trajectories. It is demonstrated that the extensions significantly improve the overall performance of the previous method in simulation on full nonlinear dynamics model of the industrial Manutec r3 robot arm. Further, it is demonstrated that it suffices to learn a policy that reaches the proximity of the goal state, from where a PI controller can be used for stable control reaching the final system state.

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Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features

arXiv

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arXiv 2024年

作者： Zelch, Christoph Peters, Jan von Stryk, Oskar Simulation Systems Optimization and Robotics Group Department of Computer Science TU Darmstadt Hochschulstr. 10 Darmstadt64289 Germany Intelligent Autonomous Systems Group Department of Computer Science TU Darmstadt Hochschulstr. 10 Darmstadt64289 Germany

Clustering of motion trajectories is highly relevant for human-robot interactions as it allows the anticipation of human motions, fast reaction to those, as well as the recognition of explicit gestures. Further, it allows automated analysis of recorded motion data. Many clustering algorithms for trajectories build upon distance metrics that are based on pointwise Euclidean distances. However, our work indicates that focusing on salient characteristics is often sufficient. We present a novel distance measure for motion plans consisting of state and control trajectories that is based on a compressed representation built from their main features. This approach allows a flexible choice of feature classes relevant to the respective task. The distance measure is used in agglomerative hierarchical clustering. We compare our method with the widely used dynamic time warping algorithm on test sets of motion plans for the Furuta pendulum and the Manutec robot arm and on real-world data from a human motion dataset. The proposed method demonstrates slight advantages in clustering and strong advantages in runtime, especially for long trajectories. Copyright © 2024, The Authors. All rights reserved.

关键词： Clustering algorithms

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Sequentially Pruning Phase Rebalance Schedule: Load Profile Learning Approach

Sequentially Pruning Phase Rebalance Schedule: Load Profile ...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Miroslav Kosanic Hongbo Sun Shunsuke Kawano Arvind Raghunathan Shoichi Kitamura Dept. of Electrical Engineering Massachusetts Institute of Technology Cambridge MA USA Optimization and Intelligent Robotics Mitsubishi Electric Research Labs Cambridge MA USA Advanced R&D Technology Center Mitsubishi Electric Corporation Amagasaki Japan

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

As low-voltage (LV) distribution networks evolve with the rise of prosumer behavior, traditional reactive load management strategies fall short of addressing the voltage phase imbalances caused by unpredictable load variations. Voltage imbalances pose significant risks including inefficiency, power outages, and equipment failures. Existing optimization solutions lack the adaptability to address this problem extensively with such dynamic environments due to the computational time budget limit. In response, this paper presents a novel method utilizing an Imitation Learning (IL) framework implemented through Ensemble Random Forests to prune the process of sequential load phase swapping, previously determined by solely running at all times costly multi-objective optimization. We maximize classifier recall performance to ensure reliable pruning. Tested across various Solar Photovoltaic (PV) penetration levels (30-100%) on a standard 13-bus LV test feeder, our method demonstrates substantial improvements in mitigating voltage imbalance, reducing operational costs, and decreasing feeder testing time by 83%. This marks a significant step forward in smart grid technology, offering utilities a robust tool to enhance system reliability with considerable time efficiency.

关键词： Schedules Europe Stochastic processes Voltage Load management Smart grids Reliability optimization Load modeling Testing

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Proactive Sequential Phase Swapping Scheduling for Distribution Systems with a Finite Horizon

Proactive Sequential Phase Swapping Scheduling for Distribut...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Hongbo Sun Miroslav Kosanic Shunsuke Kawano Arvind Raghunathan Shoichi Kitamura Yusuke Takaguchi Optimization and Intelligent Robotics Mitsubishi Electric Research Labs Cambridge MA USA Dept. of Electrical Engineering Massachusetts Institute of Technology Cambridge MA USA Advanced R&D Technology Center Mitsubishi Electric Corporation Amagasaki Japan

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

As renewable energy sources and plug-in electric vehicles increasingly penetrate power distribution systems, phase imbalance becomes more prevalent, posing significant challenges for electric utilities. This paper proactively tackles this issue by implementing phase swapping sequentially at strategic time steps and locations to improve long-term operational cost savings within a given scheduling horizon. An offline data-driven phase-swapping scheduler is developed, mimicking multi-step phase-swapping optimization through an imitation learning framework via supervised learning using random forest regression. This scheduler determines the time steps and associated loads and generations requiring phase swapping. The phase swapping over the finite scheduling horizon is modeled as a multi-step mixed-integer nonlinear programming problem, utilizing a generic branch-based radial load flow model that considers both wye and delta connections for loads and generations. For an upcoming scheduling horizon, the scheduler, based on forecasted generation, load, and price profiles, first identifies the time steps and loads/generations requiring phase swapping. Subsequently, the phase swapping actions for each determined time step are solved sequentially using a mixed-integer nonlinear optimization model with phase swapping at the determined locations and with determined number of swaps. Numerical experiments are conducted on the modified IEEE 13-node test feeder to validate the effectiveness of the proposed approach.

关键词： Renewable energy sources Costs Imitation learning Supervised learning Voltage Programming Random forests Load modeling Load flow Testing

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Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features

Clustering of Motion Trajectories by a Distance Measure Base...

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IEEE-RAS International Conference on Humanoid Robots

作者： Christoph Zelch Jan Peters Oskar von Stryk Department of Computer Science TU Darmstadt Hochschulstr. 10 Simulation Systems Optimization and Robotics Group Darmstadt Germany Department of Computer Science TU Darmstadt Hochschulstr. 10 Intelligent Autonomous Systems Group Darmstadt Germany

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Polytope Volume Monitoring Problem: Formulation and Solution via Parametric Linear Program Based Control Barrier Function

arXiv

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arXiv 2025年

作者： Wu, Shizhen Dong, Jinyang Fang, Xu Sun, Ning Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China The Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China

Motivated by the latest research on feasible space monitoring of multiple control barrier functions (CBFs) as well as polytopic collision avoidance, this paper studies the Polytope Volume Monitoring (PVM) problem, whose goal is to design a control law for inputs of nonlinear systems to prevent the volume of some state-dependent polytope from decreasing to zero. Recent studies have explored the idea of applying Chebyshev ball method in optimization theory to solve the case study of PVM;however, the underlying difficulties caused by nonsmoothness have not been addressed. This paper continues the study on this topic, where our main contribution is to establish the relationship between nonsmooth CBF and parametric optimization theory through directional derivatives for the first time, so as to solve PVM problems more conveniently. In detail, inspired by Chebyshev ball approach, a parametric linear program (PLP) based nonsmooth barrier function candidate is established for PVM, and then, sufficient conditions for it to be a nonsmooth CBF are proposed, based on which a quadratic program (QP) based safety filter with guaranteed feasibility is proposed to address PVM problems. Finally, a numerical simulation example is given to show the efficiency of the proposed safety filter. © 2025, CC BY.

关键词： Chebyshev filters

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Feature Enhancement and Reweighting for Transformer-Based Change Detection

Feature Enhancement and Reweighting for Transformer-Based Ch...

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Chinese Automation Congress (CAC)

作者： Sicheng Shao Zheng Lu Bin Zhang Xuetao Zhang Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China Institute of Remote Sensing Satellite China Academy of Space Technology School of Software Xi’an Jiaotong University Zhengzhou Key Laboratory of Intelligent Assembly Manufacturing and Logistics Optimization

关键词： Computer vision Automation Transformers Feature extraction Complexity theory Context modeling

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