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Dual-beam photothermal material trace detection method based on self-mixing interference

Applied Optics 2025年第16期64卷 4549-4558页

作者： Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach $8.0 \times {10^{- 8}}\;{\rm mol/L}$ . This method does not require labeling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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A Transfer Gated Recurrent Unit Model for Battery Health Monitoring Under Cross-Domain Conditions

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Tian, Jilun Xie, Jiale Zhang, Jiusi Huang, Congsheng Jiang, Yuchen Luo, Hao Chow, Mo-Yuen Yin, Shen Harbin Institute of Technology School of Astronautics Department of Control Science and Engineering Harbin150001 China North China Electric Power University Department of Automation Baoding071003 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Norwegian University of Science and Technology Faculty of Engineering Department of Mechanical and Industrial Engineering Trondheim7034 Norway

Battery health monitoring is crucial for ensuring maintenance reliability and safety, with broad applications in various industrial systems. Data-driven state-of-health (SOH) estimation methods can perform excellently using massive historical data without prior physical knowledge. In the battery aging process, this article extracts the essential health indicators to construct the model and adopts a suitable data preprocessing method to reduce the influence of noise. There is still a limitation for data-driven methods regarding data quality, and the domain shift caused by different operating conditions will damage estimation performance. To tackle the issue, this article proposes a transfer feature transformation (TFT) based on mean maximum discrepancy (MMD) to get a new feature space to get domain-invariant features with sufficient information. We propose a multilayer gated recurrent unit (GRU) neural network with fully connection (FC) layers to uncover hidden relationships in degraded data. Fusing TFT and GRU-FCs methods can realize an end-to-end SOH estimation under cross-domain conditions. We apply real-world public Center of Advanced Life Cycle engineering (CALCE) and NASA battery datasets and lab testing-based accelerated aging data to validate the performance of algorithms. By comparison, our proposed TFT-GRU-FCs method can get the best performance of all algorithms, and we have also given sufficient results as support. © 1963-2012 IEEE.

关键词： Electronic health record

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Multimodal Image Matching based on Frequency-domain Information of Local Energy Response

arXiv

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arXiv 2025年

作者： Yang, Meng Chen, Jun Gong, Wenping Wei, Longsheng Tian, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China Electronic Information School Wuhan University Wuhan430072 China

Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a method based on Frequency-domain Information of Local Energy Response called FILER. The core of FILER is the local energy response model based on frequency-domain information, which can overcome the effect of nonlinear intensity differences. To improve the robustness to local nonlinear geometric distortions and noises, we design a new edge structure enhanced feature detector and convolutional feature weighted descriptor, respectively. In addition, FILER overcomes the sensitivity of the frequency-domain information to the rotation angle and achieves rotation invariance. Extensive experiments multimodal image pairs show that FILER outperforms other state-of-the-art algorithms and has good robustness and *** Codes 68U10 (Primary), 68T45, 68Wxx (Secondary) Copyright © 2025, The Authors. All rights reserved.

关键词： Mathematical transformations

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Identification and control of Industrial Hydraulic Actuators with a Hammerstein-Wiener Model Approach 1st

Identification and Control of Industrial Hydraulic Actuators...

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Mohamad Ali, Nur Husnina Jaafar, Hazriq Izzuan Ghazali, Rozaimi Ghani, Muhamad Fadli Soon, Chong Chee Has, Zulfatman Fakulti Teknologi dan Kejuruteraan Elektrik Universiti Teknikal Malaysia Melaka Melaka Malaysia Center for Robotics and Industrial Automation Universiti Teknikal Malaysia Melaka Melaka Malaysia Department of Control and Mechatronics Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Penang Branch Campus Pulau Pinang Malaysia Electrical Engineering Department University of Muhammadiyah Malang Malang Indonesia

ISBN: (纸本)9789819646128

In motion control applications, the precise regulation of Industrial Hydraulic Actuators (IHA) is essential for properly ascertaining the position of the actuator rod. This research used a Hammerstein-Wiener (HW) model to characterize the system, integrating a dead zone to account for nonlinearities and using an open-loop methodology. A grey-box modelling technique is used for estimating the discrete-time model of the system and identifying its parameters. The System Identification toolbox in MATLAB functions as the principal instrument for model estimation, using input-output data acquired via experimental procedures. The validation of the input-output data demonstrated a promising best-fit percentage of 88.21%, indicating a robust connection between the HW model and the real system. To assess the trajectory tracking efficacy of the system, Proportional-Integral-Derivative (PID) and Fractional Order PID (FOPID) controllers developed and evaluated using both simulation and experimental data based on a multi-sinusoidal trajectory. The findings indicate that the FOPID controller surpasses the traditional PID controller, producing reduced Mean Square Error (MSE) and Root Mean Square Error (RMSE) values. In simulations, the FOPID control technique enhanced MSE by 32.8% and RMSE by 18.0% relative to the PID controller, although the experimental findings indicated improvements of 31.9% and 17.5%, respectively. The results highlight the superior efficacy of the FOPID controller in improving trajectory tracking performance owing to its greater complexity and flexibility. Future research may concentrate on developing more sophisticated controllers, including intelligent or nonlinear variants, to enhance the tracking precision of the IHA system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Three term control systems

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Open and Closed Source Models for LLM-Generated Metaheuristics Solving engineering Optimization Problem 28th

Open and Closed Source Models for LLM-Generated Metaheuris...

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28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Senkerik, Roman Viktorin, Adam Kadavy, Tomas Kovac, Jozef Janku, Peter Pekar, Libor Guzowski, Hubert Smolka, Maciej Byrski, Aleksander Pluhacek, Michal A.I.Lab Faculty of Applied Informatics Tomas Bata University Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University Zlin Czech Republic Faculty of Computer Science AGH University of Krakow Krakow Poland Center of Excellence in Artificial Intelligence AGH University of Krakow Krakow Poland

ISBN: (纸本)9783031900648

This paper explores the applicability of generative AI (genAI), specifically Large Language Models (LLMs), for the automatic generation and configuration of metaheuristic algorithms to address a real-world engineering problem: the optimal parameter estimation of time-delay systems in interconnected heating-cooling loops. The study introduces a pioneering workflow and iterative architecture with feedback within the emerging field of genAI-driven optimization for real optimization problems, eliminating the need for manually crafted or modified algorithms. This automated system empowers domain experts in engineering to solve complex optimization problems with minimal knowledge of optimization algorithms, lowering the barrier to entry for sophisticated algorithm use. We demonstrate how LLMs can generate effective optimizers under conditions like connstrained optimization problems where the solution lies near the boundaries of the search space. Four state-of-the-art LLMs (closed and open-sourced) have been selected for experiments. These are GPT-4o, GPT-4o mini, Claude Sonnet 3.5 and Llama 3.1. All studied LLMs generated metaheuristics that outperformed the initialization baseline optimization method (Random Search and CMA-ES). Notably, the Claude Sonnet 3.5 model generated a metaheuristic with the best mean results, almost matching the performance of the tuned state-of-the-art DISH algorithm, as an example of adaptive Differential Evolution. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Time of arrival

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UGNA-VPR: A Novel Training Paradigm for Visual Place Recognition Based on Uncertainty-Guided NeRF Augmentation

arXiv

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arXiv 2025年

作者： Shen, Yehui Zhang, Lei Li, Qingqiu Zhao, Xiongwei Wang, Yue Lu, Huimin Chen, Xieyuanli College of Intelligence Science and Technology National University of Defense Technology China Faculty of Robot Science and Engineering Northeastern University China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University China SIASUN Robot& Automation Co. Ltd China School of Computer Science Fudan University China

Visual place recognition (VPR) is crucial for robots to identify previously visited locations, playing an important role in autonomous navigation in both indoor and outdoor environments. However, most existing VPR datasets are limited to single-viewpoint scenarios, leading to reduced recognition accuracy, particularly in multi-directional driving or feature-sparse scenes. Moreover, obtaining additional data to mitigate these limitations is often expensive. This paper introduces a novel training paradigm to improve the performance of existing VPR networks by enhancing multi-view diversity within current datasets through uncertainty estimation and NeRF-based data augmentation. Specifically, we initially train NeRF using the existing VPR dataset. Then, our devised self-supervised uncertainty estimation network identifies places with high uncertainty. The poses of these uncertain places are input into NeRF to generate new synthetic observations for further training of VPR networks. Additionally, we propose an improved storage method for efficient organization of augmented and original training data. We conducted extensive experiments on three datasets and tested three different VPR backbone networks. The results demonstrate that our proposed training paradigm significantly improves VPR performance by fully utilizing existing data, outperforming other training approaches. We further validated the effectiveness of our approach on self-recorded indoor and outdoor datasets, consistently demonstrating superior results. Our dataset and code have been released at https://***/nubot-nudt/UGNA-VPR. Copyright © 2025, The Authors. All rights reserved.

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Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 247-257页

作者： Jiajun Wang Tufan Kumbasar the School of Automation Hangzhou Dianzi University IEEE the Control and Automation Engineering Department Faculty of Electrical and Electronics EngineeringIstanbul Technical University

Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs.

关键词： Big bang-big crunch (BBBC) interval type-2 fuzzy neural networks (IT2FNNs) parameter optimization particle swarm optimization (PSO)

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Semidefinite programming for manipulating acoustic traps in real time (SMART)

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Scientific Reports 2025年第1期15卷 1-26页

作者： Zehnter, Sebastian Endres, Kevin Kronbichler, Martin Andrade, Marco A. B. Funke, Felix Ament, Christoph Chair of Control Engineering University of Augsburg Augsburg 86159 Germany Chair of High-Performance Scientific Computing University of Augsburg Augsburg 86159 Germany Faculty of Mathematics Ruhr University Bochum Bochum 44801 Germany Institute of Physics University of São Paulo São Paulo 05508-090 Brazil

Sound waves can be used for trapping and manipulating objects immersed in liquids or air. However, most acoustic levitation techniques are limited to particles with diameters much smaller than the acoustic wavelength or require time-consuming optimisation-based methods that hinder the dynamic manipulation of objects. Here, we present an approach based on semidefinite programming to manipulate levitated objects in real time. To demonstrate this technique, a phased array consisting of 256 ultrasonic transducers operating at 40 kHz is used for rotating a non-spherical Rayleigh object or to translate Mie spheres along various trajectories. In contrast to previous optimisation-based approaches, the proposed method can determine the emission phases of each transducer in real time, strongly facilitating the implementation of a model-based closed-loop control in future acoustic levitation systems. This is a fundamental step for manipulating levitated objects precisely and at high speeds. © The Author(s) 2025.

关键词： Acoustic levitation Acoustic traps Block-coordinate minimisation Burer–Monteiro method Contactless handling Phase recovery Phase retrieval problem Real time Semidefinite programming Sound pressure field

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Design and Analysis of Individually Demagnetized Power Converter for Switched Reluctance Motors

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8439-8449页

作者： Liu, Hemiao Chen, Hao Wang, Xing Gorbounov, Yassen Wheeler, Patrick Anuchin, Alecksey Demidova, Galina Korovkin, Nikolay Liudmila, Sakhno Shenzhen Research Institute China University of Mining and Technology Shenzhen515100 China School of Electrical Engineering China University of Mining and Technology Xuzhou221116 China Xinjiang Institute of Engineering Xinjiang Urumqi830000 China International Joint Research Center of Central and Eastern European Countries on New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China International Cooperation Joint Laboratory of New Energy Power Generation and Electric Vehicles of Jiangsu Province Colleges and Universities Xuzhou221008 China Xuzhou Key Laboratory of New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China Department of Automation Mining Production University of Mining and Geology St. Ivan Rilski Sofia1700 Bulgaria School of Electrical Engineering University of Nottingham University Park Campus Nottingham United Kingdom Moscow111250 Russia Faculty of Control Systems and Robotics Engineer Saint-Petersburg National Research University of Information Technologies Mechanics and Optics Saint Petersburg197101 Russia Institute of Energy Peter the Great Saint-Petersburg Polytechnic University Saint Petersburg195251 Russia

Switched reluctance motors (SRMs) are capable of operating at high speeds and high loads. However, the large back-EMF results in the excitation winding current being demagnetized more slowly, which in turn reduces the efficiency and output of the motor system. This study proposes a novel individually demagnetization power converter (IDPC) specifically designed for SRMs to effectively utilize the demagnetization energy through an independent demagnetization circuit. Compared with traditional converters, the IDPC can accept direct current (DC) and high-frequency alternating current (AC) inputs while achieving fast demagnetization and energy recovery. The topology and working principle of the IDPC are analyzed in detail in this paper using a three-phase 12/8 SRM as the research object. In addition, the influence of the winding demagnetization voltage on the negative torque during the demagnetization phase was studied, as well as the functional implementation and logic control strategy of the IDPC. Simulation and experimental results confirm the validity of the proposed topology and high-frequency AC drive characteristics, as well as their advantages in terms of efficiency, output capacity and dynamic performance. © 2015 IEEE.

关键词： Reluctance motors

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Discrete-time Formation control With Attitude Alignment: A Geometric Approach under Ergodic Products

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IEEE Transactions on control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

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