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SSRN 2023年

作者： Song, Jiayin Lu, Chao Zhao, Pengpeng Song, Wenlong Fan, Yiming Huang, Qiqi Jiang, Zhuoyuan Liao, Ting Wang, Chuangqi Zhu, Yuhan Zhou, Jiancai College of Computer and Control Engineering Northeast Forestry University He Xing Road Heilongjiang Harbin150040 China Shanghai Electric Power Company State Grid Yuan Shen Road Shanghai200122 China

This paper proposes an Enhanced Slime Mould algorithm (ESMA) for solving the multi-objective optimal scheduling problem in microgrids (MG). The ESMA combines the Slime Mould Algorithm (SMA) with the Equilibrium Optimizer (EO). The MG optimal scheduling problem is formulated as a nonlinearly constrained optimization problem, considering three objective functions: management cost, pollution treatment cost, and cut-off load cost, along with multiple constraints. The performance of the ESMA algorithm is verified by testing on 12 benchmark test functions and then compared with the Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and SMA algorithms under identical conditions. The results demonstrate that the SMA algorithm exhibits an advantage in achieving the optimal value. Subsequently, the ESMA algorithm is applied to the off/on-grid dispatching scheme, where the weights of the multiple objective functions in the optimization scheme are determined using the ESMA-fuzzy AHP algorithm. Simulation results illustrate that the ESMA algorithm effectively fulfills the load demand within the MG while minimizing the operational cost through appropriate power output deployment and flexible load adjustment. This ensures the economic viability and power supply reliability of the MG operation. © 2023, The Authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

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Highly responsive nonlinear sensor by tracking a Hamiltonian hopping point

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Photonics Research 2024年第10期12卷 2235-2241页

作者： ZHU LIU YIKUAN DENG XI TIAN ZHIPENG LI Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory of Physics and Devices in Post-Moore EraCollege of Hunan ProvinceSchool of Physics and ElectronicsHunan Normal UniversityChangsha 410081China Tsinghua-Berkeley Shenzhen Institute Institute of Data and InformationShenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

Responsivity is a critical parameter for sensors utilized in industrial miniaturized sensors and biomedical implants,which is typically constrained by the size and the coupling with external reader,hindering their widespread applications in our daily ***,we propose a highly-responsive sensing method based on Hamiltonian hopping,achieving the responsivity enhancement by 40 folds in microscale sensor detection compared to the standard *** implement this sensing method in a nonlinear system with a pair of coupled resonators,one of which has a nonlinear ***,our method surpasses the sensing performance at an exceptional point(EP)—simultaneous coalescence of both eigenvalues and *** responsivity of our method is notably enhanced thanks to the large frequency response at a Hamiltonian hopping point(HHP)in the strong coupling,far from the *** study also reveals a linear HHP shift under different perturbations and demonstrates the detection capabilities down to sub-picofarad(<1 pF)of the microscale pressure sensors,highlighting their potential applications in biomedical implants.

关键词： Hamiltonian nonlinear point

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Performance Analysis of Distributed Filtering under Mismatched Noise Covariances

arXiv

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arXiv 2024年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The Laboratory of Security Operation and Control for Intelligent Autonomous Systems Department of Systems Science School of Mathematics Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper systematically investigates the performance of consensus-based distributed filtering under mismatched noise covariances. First, we introduce three performance evaluation indices for such filtering problems, namely the standard performance evaluation index, the nominal performance evaluation index, and the estimation error covariance. We derive difference expressions among these indices and establish one-step relations among them under various mismatched noise covariance scenarios. We particularly reveal the effect of the consensus fusion on these relations. Furthermore, the recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these indices under the collective observability condition, and show this convergence condition of the nominal performance evaluation index can guarantee the convergence of the estimation error covariance. Additionally, we prove that the estimation error covariance of the consensus-based distributed filter under mismatched noise covariances can be bounded by the Frobenius norms of the noise covariance deviations and the trace of the nominal performance evaluation index. Finally, the effectiveness of the theoretical results is verified by numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Wiener filtering

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Brain-inspired feedback for spatial frequency aware artificial networks

Brain-inspired feedback for spatial frequency aware artifici...

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Asilomar Conference on Signals, Systems & computers

作者： Ramin Toosi Mohammad Ali Akhaee Mohammad-Reza A. Dehaqani School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Cognitive Systems Laboratory Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran

Spatial frequency (SF) is a characteristic of an image that could dissociate course and fine shape information. Physiological and psychophysical studies widely investigated the role of various SF contents in image processing. Inspired by the primate brain structure, deep neural networks improved various computer vision tasks such as image classification. Physiological studies show that low SF (LSF) contents of an image could be processed faster to provide feedback to facilitate object recognition. However, this knowledge has not been considered in designing neural network structures. This study introduces SFNet, a new neural network structure that employs an LSF-based feedback mechanism. SFNet is a two-stream structure where one stream is used for LSF processing to provide feedback for image classification. The other stream combines the LSF-based feedback and the HSF processing to form the final decision. The role of the proposed LSF-based feedback in image classification is investigated utilizing the CIFAR100 dataset. The results show that SFNet improves the performance in the presence of SF filtering compared to the equivalent structures.

关键词： Band-pass filters Visualization Shape Filtering Streaming media Visual systems Physiology

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Perceptual Quality Assessment of Trisoup-Lifting Encoded 3D Point Clouds

arXiv

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arXiv 2024年

作者： Long, Juncheng Su, Honglei Liu, Qi Yuan, Hui Gao, Wei Song, Jiarun Wang, Zhou The College of Electronics and Information Qingdao University Qingdao266071 China The School of Control Science and Engineering Shandong University Ji'nan250061 China The School of Electronic and Computer Engineering Peking University Shenzhen518055 China The Peng Cheng Laboratory Shenzhen518066 China The School of Telecommunications Engineering Xidian University Xi'An710071 China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

No-reference bitstream-layer point cloud quality assessment (PCQA) can be deployed without full decoding at any network node to achieve real-time quality monitoring. In this work, we develop the first PCQA model dedicated to Trisoup-Lifting encoded 3D point clouds by analyzing bitstreams without full decoding. Specifically, we investigate the relationship among texture bitrate per point (TBPP), texture complexity (TC) and texture quantization parameter (TQP) while geometry encoding is lossless. Subsequently, we estimate TC by utilizing TQP and TBPP. Then, we establish a texture distortion evaluation model based on TC, TBPP and TQP. Ultimately, by integrating this texture distortion model with a geometry attenuation factor, a function of trisoupNodeSizeLog2 (tNSL), we acquire a comprehensive NR bitstream-layer PCQA model named streamPCQ-TL. In addition, this work establishes a database named WPC6.0, the first and largest PCQA database dedicated to Trisoup-Lifting encoding mode, encompassing 400 distorted point clouds with both 4 geometric multiplied by 5 texture distortion levels. Experiment results on M-PCCD, ICIP2020 and the proposed WPC6.0 database suggest that the proposed streamPCQ-TL model exhibits robust and notable performance in contrast to existing advanced PCQA metrics, particularly in terms of computational cost. The dataset and source code will be publicly released at https://***/qdushl/Waterloo-Point-Cloud-Database-6.0. Copyright © 2024, The Authors. All rights reserved.

关键词： Encoding (symbols)

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Perceptual Quality Assessment of Octree-RAHT Encoded 3D Point Clouds

arXiv

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arXiv 2024年

作者： Duan, Dongshuai Su, Honglei Liu, Qi Yuan, Hui Gao, Wei Song, Jiarun Wang, Zhou College of Electronics and Information Qingdao University Qingdao266071 China School of Control Science and Engineering Shandong University Ji’nan250061 China School of Electronic and Computer Engineering Peking University Shenzhen518055 China Peng Cheng Laboratory Shenzhen518066 China School of Telecommunications Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

No-reference bitstream-layer point cloud quality assessment (PCQA) can be deployed without full decoding at any network node to achieve real-time quality monitoring. In this work, we focus on the PCQA problem dedicated to Octree-RAHT encoding mode. First, to address the issue that existing PCQA databases have a small scale and limited distortion levels, we establish the WPC5.0 database which is the first one dedicated to Octree-RAHT encoding mode with a scale of 400 distorted point clouds (PCs) including 4 geometric multiplied by 5 attitude distortion levels. Then, we propose the first PCQA model dedicated to Octree-RAHT encoding mode by parsing PC bitstreams without full decoding. The model introduces texture bitrate (TBPP) to predict texture complexity (TC) and further derives the texture distortion factor. In addition, the Geometric Quantization Parameter (PQS) is used to estimate the geometric distortion factor, which is then integrated into the model along with the texture distortion factor to obtain the proposed PCQA model named streamPCQ-OR. The proposed model has been compared with other advanced PCQA methods on the WPC5.0, BASICS and M-PCCD databases, and experimental results show that our model has excellent performance while having very low computational complexity, providing a reliable choice for time-critical applications. To facilitate subsequent research, the database and source code will be publicly released at https://***/qdushl/Waterloo-Point-Cloud-Database-5.0. Copyright © 2024, The Authors. All rights reserved.

关键词： Database systems

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Fast Finite-Time Adaptive Neural control for Pure-Feedback Stochastic Nonlinear Systems

Fast Finite-Time Adaptive Neural Control for Pure-Feedback S...

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Memristive Computing and Applications (ICMCA), IEEE International Conference on

作者： Ximei Zhao Hanyu Zhang Lijun Shao Lili Huang Jiao Li School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Collaborative Innovation Center of Memristive Computing Application(CICCA) Qilu Institute of Technology Jinan China College of Computer and Communication Engineering Qilu Institute of Technology Jinan China

In this article, we solve the fast finite-time stabilization as well as adaptive neural control design issues for a class uncertain stochastic nonlinear systems. By employing the mean value theorem, the pure-feedback form can be transformed into strict-feedback case. Firstly, a new fast finite-time control scheme is proposed in virtue of generalizing the fast finite-time adaptive control strategy for deterministic systems to the stochastic case. Next, a novel adaptive neural control strategy is developed to simultaneously deal with the stochastic nonlinear systems with completely unknown nonlinearities as well as the disturbances term. Then, stability analysis have been given based on a Jensen's inequality.

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Current-Constrained Finite-Time control Scheme for Speed Regulation of PMSM Systems With Unmatched Disturbances

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IEEE Transactions on Automation Science and engineering 2025年 22卷 16877-16887页

作者： Huiming Wang Zhize Zhang Yingjie Luo Junxiao Wang Jiankun Sun Yunda Yan Xianlun Tang Chongqing Key Laboratory of Complex Systems and Autonomous Control Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing China College of Information Engineering Zhejiang University of Technology Hangzhou China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Department of Computer Science University College London London U.K.

The article investigates the speed regulation of permanent magnet synchronous motor (PMSM) systems. Existing control methods of the non-cascade structure suffer from the drawbacks of unsatisfactory anti-disturbance performance and slow convergence rate when the system is affected by disturbances, especially unmatched disturbances. Meanwhile, the requirements of current constraint and fast dynamics cannot be effectively balanced in the single-loop structure of speed and current using traditional control methods such as the PID controller. Because large transient currents induced by fast dynamics may damage the hardware of the system. Therefore, a current-constrained finite-time control approach is proposed. Specifically, a robust finite-time control scheme is developed with the assistance of the improved finite-time observer technique. The proposed method is capable of actively suppressing both matched and unmatched disturbances in non-cascade control systems. Simultaneously, an effective penalty mechanism is established to incorporate a specific gain function into the designed controller. This approach restricts the q-axis current to a predefined safe range without solving an optimization problem. Finally, comparative experiment results indicate that the newly proposed finite-time control method outperforms the baseline control methods in terms of disturbance rejection, convergence rate, and current constraint. Note to Practitioners—This paper addresses practical challenges in controlling permanent magnet synchronous motor (PMSM) systems, such as ensuring robust disturbance rejection while limiting transient currents to protect the hardware. Traditional methods often fail to balance fast dynamics with current constraints, leading to inefficiencies and potential damage. To tackle these issues, the proposed finite-time control approach introduces a practical solution that achieves robust disturbance rejection while ensuring that transient currents remain within safe o

关键词： Convergence Observers control systems Automation Transient analysis Asymptotic stability Stability analysis Regulation Permanent magnet motors Optimization

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Path Planning and controlling of Omni-Directional Robot Using Cartesian Odometry and PID Algorithm

Path Planning and Controlling of Omni-Directional Robot Usin...

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2019 International Conference on Computing, Power and Communication Technologies, GUCON 2019

作者： Chaudhari, Tejas Jha, Mayank Bangal, Rohit Chincholkar, Ganesh Govt. College of Engineering and Research Department of Instrumentation and Control Engineering Pune India Govt. College of Engineering and Research Department of Computer Engineering Pune India

ISBN: (纸本)9789353510985

Omni direction is the concept of existence of motion in every direction. Here, we have controlled the resulting vectors of individual wheels of a three wheel omni robot that are ultimately responsible for a stabilized motion of the robot in any direction. This phenomenon is termed as 'Holonomic Drive' and it provides higher efficiency and controllability to non-holonomic drives, when used with odometry and PID algorithms. Odometry basically is method of acquiring the real time positional data of a system in a world frame and using it for path planning. PID algorithm when applied on any system reduces the transient response and helps to attend steady state conditions with less settling time. Here, we have successfully designed and implemented the algorithms for path planning with the help of quadrature encoders and heading control of three wheel omni robot using PID, implemented on IMU(Inertial Measurement Unit). © 2019 Galgotias University.

关键词： Motion planning

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Lightweight Trust Model with Machine Learning scheme for secure privacy in VANET 18

Lightweight Trust Model with Machine Learning scheme for sec...

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18th International Learning and Technology Conference, L and T 2021

作者： Junejo, Muhammad Haleem Ab Rahman, Ab Al-Hadi Shaikh, Riaz Ahmed Yusof, Kamaludin Mohamad Kumar, Dileep Memon, Imran Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Skudai81310 Malaysia Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Department of Computer Science Bahria University Karachi campus sindh Pakistan

A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET. © 2021 The Authors. Published by Elsevier B.V.

关键词： Machine learning

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