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Image-denoising algorithm based on improved K-singular value decomposition and atom optimization

CAAI Transactions on Intelligence Technology 2022年第1期7卷 117-127页

作者： Rui Chen Dong Pu Ying Tong Minghu Wu College of Information&Communication Engineering Nanjing Institute of TechnologyNanjingChina College of Electric Power Engineering Nanjing Institute of TechnologyNanjingChina Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of technologyWuhanChina

The traditional K-singular value decomposition(K-SVD)algorithm has poor imagedenoising performance under strong *** image-denoising algorithm is proposed based on improved K-SVD and dictionary atom ***,a correlation coefficient-matching criterion is used to obtain a sparser representation of the image *** dictionary noise atom is detected according to structural complexity and noise intensity and removed to optimize the ***,non-local regularity is incorporated into the denoising model to further improve image-denoising *** of the simulated dictionary recovery problem and application on a transmission line dataset show that the proposed algorithm improves the smoothness of homogeneous regions while retaining details such as texture and edge.

关键词： singular value smoothness

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Transferable Intervalization and Midpoint De-Mixing Interval Independent Component Analysis for Industrial Fault Detection Under Data Uncertainty

SSRN

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SSRN 2024年

作者： Zhang, Shumei Wang, Sijia Dong, Feng Zhao, Chunhui Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University Tianjin373200 China School of Information and Intelligent Engineering Tianjin Renai College Tianjin301636 China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China

Due to noise disturbance, sensor drift, and some circumstance factors, process data are unavoidably contaminated with uncertainty, which may destroy the correlation structure of original data and make traditional process monitoring methods perform poorly. In this study, a transferable Gaussian mixture learning (TGML) method is developed to make full use of the important knowledge extracted from source domains to guide and improve the intervalization process of target domain with limited data. Then, a midpoint de-mixing interval independent component analysis (MDM-I2CA) is proposed for non-Gaussian processes with uncertainty. First, MDM-I2CA expands the traditional centering and whitening methods into interval domain to concentrate the data information on higher-order statistics. Second, a midpoint coding strategy is developed to depict the process information with the idea of focusing on the variation between intervals of a dataset, and the statistically interval independent components are further de-mixed. Finally, four monitoring statistics are constructed for fault detection. © 2024, The Authors. All rights reserved.

关键词： Fault detection

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A fault isolation method using kernel canonical variate analysis-based contribution

A fault isolation method using kernel canonical variate anal...

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第35届中国过程控制会议

作者： Hongxin Wang Lingxia Mu Nan Feng Han Liu Ding Liu Department of Information and Control Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology School of Intelligence Science and Technology University of Science and Technology Beijing

Fault diagnosis and isolation is important for industrial system. In this paper, a kernel canonical variate analysis(KCVA) is proposed for fault isolation. KCVA is originally used as a data dimension reduction technique which can account for nonlinearity and correlations in the industrial dynamical process data. But there are some difficulties using KCVA in the construction of the contribution for the fault isolation. On the one hand, it is difficult to compute the contributions of individual variables because it is scarcely possible to find an inverse mapping from the feature space to the original space. On the other hand, a smearing effect is hardly avoided. To solve the problem, a KCVA-based contributions is proposed using the state subspace and the residual subspace which can isolate the faulty variables effectively. Simulations are conducted on the Tennessee Eastman process to verify the performance of the proposed method.

关键词： Kernel canonical variate analysis contribution plot fault isolation

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On the Equilibrium of a Class of Leader-Follower Games with Decision-Dependent Chance Constraints

arXiv

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arXiv 2024年

作者： Wang, Jingxiang Wang, Zhaojian Yang, Bo Liu, Feng Guan, Xinping The Key Laboratory of System Control and Information Processing Ministry of Education of China The Department of Automation Shanghai Jiao Tong University Shanghai China The State Key Laboratory of Power System The Department of Electrical Engineering Tsinghua University Beijing100084 China

In this paper, we study the existence of equilibrium in a single-leader-multiple-follower game with decision-dependent chance constraints (DDCCs), where decision-dependent uncertainties (DDUs) exist in the constraints of followers. DDUs refer to the uncertainties impacted by the leader’s strategy, while the leader cannot capture their exact probability distributions. To address such problems, we first use decision-dependent ambiguity sets under moment information and Cantelli’s inequality to transform DDCCs into second-order cone constraints. This simplifies the game model by eliminating the probability distributions. We further prove that there exists at least one equilibrium point for this game by applying Kakutani’s fixed-point theorem. Finally, a numerical example is provided to show the impact of DDUs on the equilibrium of such game models. Copyright © 2024, The Authors. All rights reserved.

关键词： Game theory

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MMFOSOM: A Novel Multi-objective Moth–Flame Optimization Algorithm Based on Self-Organizing Mapping

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International Journal of Computational Intelligence systems 2025年第1期18卷 1-22页

作者： Li, Zhifu Zheng, Ziyang Ni, Chengkai Li, Mingzong School of Mechanical and Electrical Engineering Guangzhou University Guangzhou China Guangdong-Hong Kong-Macao Key Laboratory of Multi-Scale Information Fusion and Collaborative Optimization Control of Complex Manufacturing Process Guangzhou University Guangzhou China

An optimization technique seeks to identify the best solution for a given problem. When the problem involves a single objective function, the optimal solution yields the best value for that objective. However, in cases with multiple objectives, selecting the best solution becomes more complex, as these objective functions often conflict with one another. For such multi-objective optimization problems, relying on analytical or exact methods is often not feasible. This paper proposes a modified MFO called multi-objective moth–flame optimization based on self-organizing mapping (MMFOSOM) to solve multi-objective optimization problems. For attaining high-quality initial moths, dual opposition-based learning mechanism is employed to generate two distinct populations, referred to as the exploration moth (EM) and the auxiliary moth (AM). In order to enhance the search capabilities of the algorithm, each population is assigned a SOM network, the adaptive neighborhood structure of which contributes to forming modal clusters in the mapping, organizing similar solutions together. In order to select the excellent individual as the training data for SOM, a novel environmental selection mechanism is introduced. To validate the effectiveness of the algorithm, experiments will be conducted on a set of multi-objective optimization test functions. The experimental results indicate that the proposed algorithm can effectively address multi-objective optimization problems.

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Modeling and Parameter Identification of Constant-Speed Centrifugal Chiller Based on Experiments

Modeling and Parameter Identification of Constant-Speed Cent...

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2023 International Conference on Power system Technology, PowerCon 2023

作者： Han, Xinchan Zhang, Wen Cheng, Dingyi Zhang, Tingting Liu, Meng Xie, Yuxin Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Research Institute Jinan China JinXianDai Information Industry Co. Ltd. Jinan China

ISBN: (纸本)9798350300222

The expanding penetration of intermittent renewable energy resources is motivating the development of demand response (DR) services for balancing generation and load. Central air conditionings (CACs) are potential candidates due to their thermal energy storage capability. A suitable load model is the foundation for DR services. However, CACs contain multiple control subsystems whose parameters are difficult to obtain because of trade secrets. This paper focuses on the modeling and parameter identification of the constant-speed centrifugal chiller, which accounts for 60-70% of the power of CAC. A thermal-electrical model of a constant-speed centrifugal chiller is established to describe the dynamic operation process. In addition, the critical control parameters and the delay time of control systems are identified based on experimental data for a practical building chiller. The experimental results verified the effectiveness of the proposed model. © 2023 IEEE.

关键词： Air conditioning

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Explicit Predictive control of Forward DC-DC Converter Based on an Input-Mapping Method

Explicit Predictive Control of Forward DC-DC Converter Based...

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第43届中国控制会议

作者： Xiang Gu Dewei Li Aoyun Ma Yaru Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.

关键词： Forward DC-DC converter explicit model predictive control input-mapping method

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Lightweight Vision Transformer for Small Data Sets 38

Lightweight Vision Transformer for Small Data Sets

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Fang, Wenxing Su, Yanxu Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei230601 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects. © 2023 IEEE.

关键词： lightweight pooling self-attention windows

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Signal Temporal Logic Based Vehicle Trajectory Planning Under Mandatory Stop Rule for Heavy Vehicle Right Turns at Signal-Free Intersections

Signal Temporal Logic Based Vehicle Trajectory Planning Unde...

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International Conference on Intelligent Transportation

作者： Wanqing Zuo Yunwen Xu Youren Chen Dewei Li School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

The blind spots of heavy vehicles during right turns arise a safety concern for traffic. Hence, the regulation mandating heavy vehicles to come to a complete stop before making right turns is crucial in ensuring intersection safety. However, the current trajectory planning methods struggle to integrate these traffic regulations, and the restrictions imposed by such traffic rules greatly impact traffic efficiency at intersections. This paper proposes a signal temporal logic (STL) based trajectory planning method for connected and autonomous vehicles (CAVs) at a signal-free intersection, where traffic rules for heavy vehicles are conveniently described by STL formulas. All CAVs at the intersection are modeled without predefined paths to enhance the flexibility of trajectories. Each STL formula is encoded in a standardized way as a conjunction of inequality and equality constraints for the optimization, and the whole trajectory planning of CAVs is achieved through solving a mixed-integer nonlinear programming (MINLP) problem. Simulation results indicate that our method improves traffic efficiency in the scenario with heavy vehicles right turns.

关键词： Connected vehicles Trajectory planning Simulation Programming Regulation Trajectory Safety Planning Logic Autonomous vehicles

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Thermally Drawn Monolithic Polymer Continuum Robot with Laser Cutting Profile

Thermally Drawn Monolithic Polymer Continuum Robot with Lase...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Liu, Huanghua Zou, Yun Xu, Zheng Gao, Anzhu Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9798350325706

Continuum robots have the great potential in endoluminal diagnosis and intervention toward narrow and confined workspace. However, fabrication of continuum robots still poses a grant challenge in its miniaturization. To solve this, this paper designs a thermally drawn monolithic polymer continuum robot with laser cutting profile. First, the continuum robot is designed with two degrees of freedom (DOF) for shape deflection, and it consists of four optical fibers with the fiber Bragg grating (FBG) sensor on each for tension sensing as driving cables. Second, its main body is a multi-channel polycarbonate (PC) tube produced by thermal drawing process, and a series of rectangular cutouts are made on it via laser cutting process. By combining these two fabrication processes, the developed continuum robot realizes the integration of the multi-channel structure and the notch feature. Third, a control framework of puller-follower controller using the integrated tension sensing is proposed for teleoperation control. Finally, experimental setup is built for the robot validation, and results show that the repeated positioning accuracy of the robot is 1.08 mm. Moreover, a micro endoscope and a needle are added to the end of the continuum robot, and a phantom study of auripuncture and drug delivery is completed to verify the preliminary feasibility. And the proposed fabrication approach enables the miniaturization and complex structure for the cable-driven continuum robots. © 2023 IEEE.

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