检索结果-内蒙古大学图书馆

Real-Time Price-Based Demand Response for Industrial Manufacturing Process via Safe Reinforcement Learning

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第4期21卷 2937-2946页

作者： Ye, Xueyu Liu, Zhi-Wei Chi, Ming Ye, Lintao Li, Chaojie Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

Industrial manufacturing processes present unique challenges in implementing demand response due to their complex equipment interactions, diverse operation modes, and safety constraints. Conventional model-based optimization methods often struggle in this context, requiring complete mathematical models and accurate uncertainty distributions. In this article, we propose a model-free safe deep reinforcement learning approach for real-time scheduling of industrial manufacturing systems, ensuring constraint adherence and accommodating diverse equipment operation modes. Specifically, the approach formulates the industrial demand response problem as a constrained Markov decision process with hybrid action space, capturing the intricate interplay between variable-speed equipment and discrete actuators, while considering safety constraints. To enhance exploration and robustness, the proposed method combines Lagrange multipliers based on soft actor-critic to satisfy the constraints. The cross-attention mechanism is utilized to find the association rules between hybrid actions to solve the challenges posed by the spatial gradient of hybrid actions. The proposed approach is trained and tested on a real-world dataset, demonstrating its superior performance in achieving significant cost reductions for manufacturing while satisfying operational constraints. Furthermore, sensitivity analysis underpins robustness against the variable real-time prices, showcasing its industrial applicability.

关键词： Production Safety Real-time systems Costs Manufacturing processes Job shop scheduling Electricity Demand response Uncertainty Training Hybrid action space industrial demand response (DR) industrial manufacturing process (IMP) safe deep reinforcement learning (DRL) scheduling

来源：评论

学校读者我要写书评

暂无评论

Fixed-time synchronization in p-th moment for stochastic multi-layer neural networks: An adaptive graph-theoretic Lyapunov functional approach

引用

NEUROCOMPUTING 2025年 636卷

作者： Yu, Guan-Nan Liu, Xiao-Kang Lei, Yan Wang, Yan-Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Southwest Univ Sch Elect & Informat Engn Chongqing 400715 Peoples R China

In this paper, the p-th moment synchronization problem for a class of stochastic multi-layer neural networks with intra-layer and inter-layer connections is investigated. Due to the multiple connections with delays and stochastic noise, the typical methodologies that build a canonical linear or expanded matrix model to analyze its stability by constraining eigenvalues in the left-half plane, such as the Kronecker product method, linear matrix inequality and M-matrix approach are tough to tackle the problem. Consequently, a graph-theory-based Lyapunov functional is constructed by combining multiplicative principles and a graph-theoretic approach to help examine the effect of inter- and intra-layer connectivity on a unified framework. With the proposed adaptive fixed-time controller, sufficient conditions for the p-th moment synchronization in a fixed time are derived in terms of algebraic inequality. A corollary, together with a constant-gain fixed-time controller, is presented in case there is no delay. Finally, a confirmatory and two comparative simulations show the effectiveness and convenient implementation of the proposed control strategy.

关键词： Multi-layer network Neural networks Synchronization Fixed-time Adaptive control

来源：评论

学校读者我要写书评

暂无评论

Asynchronous Spiking Neural P Systems With Rules Working in the Rule Synchronization Mode

IEEE TRANSACTIONS ON NANOBIOSCIENCE

引用

IEEE TRANSACTIONS ON NANOBIOSCIENCE 2023年第1期22卷 3-10页

作者： Jin, Yu Zhang, Luping Zhejiang Univ Sch Math Sci Hangzhou 310058 Zhejiang Peoples R China Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China

Asynchronous spiking neural P systems with rules on synapses (ARSSN P systems) are a class of computation models, where spiking rules are placed on synapses. In this work, we investigate the computation power of ARSSN P systems working in the rule synchronization mode, where a family of rule sets are specified, and all the rules in a such set should be synchronously used or not. We prove that ARSSN P systems working in the rule synchronization mode are universal as number generating. Additionally, two universal ARSSN P systems working in the rule synchronization mode are constructed to accept numbers and compute functions, respectively. The results indicate that rule synchronization set is a powerful ingredient for resource-saving, as the constructed universal ARSSN P systems with rule synchronization sets use less neurons than the counterpart universal systems without such sets.

关键词： Neurons Synchronization Synapses Standards Nanobioscience Biomembranes Heating systems Bio-inspired computing membrane computing spiking neural P systems rule synchronization universality

来源：评论

学校读者我要写书评

暂无评论

BPR-Net: Balancing Precision and Recall for Infrared Small Target Detection

引用

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷 1页

作者： Du, Shuaiyuan Wang, Kewei Cao, Zhiguo Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Minist Educ Wuhan 430074 Peoples R China

Most current infrared small target detection methods attempt to fuse local and global information by using single-scale inputs and creating a multiscale feature pyramid during network feeding forward. Further to this, our research finds that using high-resolution inputs can improve recall, while low-resolution inputs improve precision. Nevertheless, solely focusing on global or local information can result in missing targets and false alarms. To address these issues, we propose the BPR-Net to balance precision and recall via a novel multiscale attention mechanism, which combines semantic and shallow features of multiscale inputs (MS). We first scale the input image into multiple images with varying resolutions and feed them into the network. In the encoder, the scale fusion module (SFM) fuses features from corresponding images of different resolutions. In the decoder, a channel fusion module (CFM) fuses useful information from multiple channels. Furthermore, a wavelet transform cross-layer skip layer (WTL) is employed to enhance the interaction between decoder layers for more effective multiscale feature fusion. Experimental results demonstrate that our approach achieves a balance between recall and precision and yields state-of-the-art performance on challenging benchmarks including Sirst, miss detection versus false alarm (MDvsFA), and small infrared aerial target detection (SIATD). Notably, our approach achieves an F1 score of 0.9409 on the challenging benchmark SIATD, surpassing the state-of-the-art method by 16.7%.

关键词： & nbsp Balancing precision and recall feature fusion infrared small target multiscale attention

来源：评论

学校读者我要写书评

暂无评论

Attack Intention Oriented Dynamic Risk Propagation of Cyberattacks on Cyber-Physical Power Systems

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第3期19卷 2453-2462页

作者： Hu, Bowen Zhou, Chunjie Tian, Yu-Chu Du, Xin Hu, Xiaoya Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Hubei Peoples R China Queensland Univ Technol Sch Comp Sci Brisbane Qld 4001 Australia

Advanced cyber-physical power systems (CPPS) has been put forward by the strong integration of energy networks and communication networks. While CPPS brings a promising solution with high efficiency, strong flexibility, great scalability, and improved reliability, it inevitably poses some security challenges. In order to address these challenges, it is essential to accurately describe the attack behavior and system security situation. In this article, a dynamic risk propagation evaluation approach is proposed for accurately predicting attacks and quantitatively analyzing system risk. It is equipped with a partitioned cellular automata model to deal with spatial heterogeneity in the partitioned system. The intentions of targeted attack are also considered for predicting attacks. Then, the cyber-to-physical risk is quantitatively identified from multiple dimensions. Finally, the verification of attack intention is designed to dynamically update and adjust the predicted result. The presented approach is demonstrated through a case study on a CPPS.

关键词： Computer crime Power systems Principal component analysis Analytical models Predictive models Power system dynamics Informatics Attack intention cyberattacks cyber-physical power systems (CPPS) partitioned cellular automata (PCA) risk propagation

来源：评论

学校读者我要写书评

暂无评论

Synchronization of Delayed Complex Networks on Time Scales via Aperiodically Intermittent control Using Matrix-Based Convex Combination Method

引用

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第6期34卷 2938-2950页

作者： Wan, Peng Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci Ence & Technol Minist China Key Lab Image Proc & Intelligent Control Educ Wuhan 430074 Peoples R China

This article reconsiders synchronization problem of linear complex networks with time-varying delay on time scales. For different types of time scales, aperiodically intermittent control scheme is established by using a matrix-based convex combination method, which has great potential in reducing control consumption and saving communication bandwidth. By employing a common Lyapunov function, aperiodically intermittent controllers are utilized successfully to achieve synchronization of linear delayed complex networks on special time scales onto an isolated node. Next, by constructing a special Lyapunov function with time-varying coefficients, sufficient criteria that consist of two linear matrix inequalities are demonstrated to make linear delayed complex networks on general time scales synchronized onto an isolated system with an exponential convergence rate given in advance. Due to delayed complex networks in this article defined on time scales, the proposed control schemes are applicable to continuous-time networks, their discrete-time forms, and any combination of them. Four numerical examples are offered to highlight the effectiveness and superiority of the proposed aperiodically intermittent control schemes at last.

关键词： Synchronization Complex networks Lyapunov methods Delays Time-varying systems Convergence Technological innovation Complex networks convex combination method intermittent control synchronization time scale

来源：评论

学校读者我要写书评

暂无评论

VSDHS-CIEA: Color image encryption algorithm based on novel variable-structure discrete hyperchaotic system and cross-plane confusion strategy

引用

INFORMATION SCIENCES 2024年 665卷

作者： Zhang, Hangming Hu, Hanping Ding, Weiping Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China Nantong Univ Sch Informat Sci & Technol Nantong 226019 Peoples R China

Recently, the color image encryption algorithm based on chaos theory has become the focus of current research. When encrypting color images, the common practice is to treat color images as different gray components and process them severally, which results in more redundancy and low efficiency. The security of chaotic cryptosystems also depends on the performance of the chaotic systems adopted. The structures of many current chaotic systems are fixed, making their behaviors highly predictable. Additionally, the range of chaotic region parameters is limited and discontinuous. To solve the above-mentioned problems, a new color image encryption algorithm (CIEA) using fractal and chaos theory is presented, which fully considers the inherent connection among the RGB components of color images. First, we propose a variable-structure discrete hyperchaotic system (VSDHS) to solve the dilemma encountered by existing chaotic systems. The excellent dynamic properties of VSDHS are verified by rigorous mathematical proof and simulation performance analyses. Then, VSDHS-CIEA is designed using fractal theory and VSDHS. The algorithm makes full use of the inherent connection among the different components of color images and performs cross-plane confusion. Simulations and performance analyses prove that VSDHS-CIEA has higher security and better performance than some representative image encryption algorithms.

关键词： Color image encryption Chaotic system Fractal theory Cross-plane confusion strategy Synchronous confusion-diffusion

来源：评论

学校读者我要写书评

暂无评论

Microgrid energy management strategy considering microgrid economy and rSOC stability: A model-based study 43

Microgrid energy management strategy considering microgrid e...

引用

43rd Chinese control Conference, CCC 2024

作者： Huang, Haizhou Xia, Zhiping Shan, Xinkai Wang, Jie Li, Xi Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

ISBN: (纸本)9789887581581

Microgrids possess the ability to use renewable energy efficiently and play an increasingly significant role in environmental protection and sustainable development. Meanwhile, reversible solid oxide fuel cell (rSOC) is currently a new type of energy conversion and storage. Combining with microgrid systems is a great way to benefit from its high capacity, high efficiency, and cleanliness. However, rSOC's complex system of coupled heat, electricity, and gas presents a significant challenge in finding energy management strategies for microgrid applications containing rSOC. In this study, for a microgrid system combining rSOC, battery energy storage system (BESS), solar photovoltaic (PV), and wind turbine generator (WTG), we propose a model-based energy management strategy that simultaneously takes into account the economy of the microgrid system and the stability of the rSOC system. First of all, the microgrid is modeled with great detail, including the wind turbine, solar panels, battery storage system, and rSOC. In addition, the microgrid energy management problem is framed as a mathematical programming problem, with the attention focusing on the costs of BESS aging and operational energy loss of rSOC. In particular, this study also proposes a penalty strategy to reduce the power fluctuation amplitude of the rSOC system and reduce the mode switching frequency of the rSOC system. Using the solver, solving for each device's target power in a microgrid. The actual power operating curve is output by tracking the target power under slope constraints using the Simulink model. We then conduct a case study using data from Wuhan, China. Our research shows that compared with the control strategy based on rule control, the control strategy proposed in this study can reduce the power variation amplitude of the rSOC system by 79%, reduce the mode switching frequency by 85%, reduce the system operating cost by 4.5% and increase the energy self-sufficiency rate by 9%. © 2024 Techn

关键词： Wind turbines

来源：评论

学校读者我要写书评

暂无评论

A Security and Trust Protection Framework for Open CNC Production Line

A Security and Trust Protection Framework for Open CNC Produ...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Dong, Zeyang Qin, Yuanqing Li, Zewei Wang, Hanwen Huazhong University of Science and Technology School of Artificial Intelligence and Automation MOE Lab of Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9781665465335

With the further integration of information technology and industry, the computer numerical control (CNC) production line has gradually changed from the original isolated and closed mode to an open one. It faces not only internal threats, but also threats from the Internet. Starting from the characteristics and cybersecurity problem analysis of open CNC production lines, this paper proposes a security and trust protection framework based on trusted computing 3.0 and the concept of defense in depth, where a tri-element peer architecture is introduced to realize two-way authentication between the access device and the platform and an active immunity scheme for open CNC system is designed to ensure the trust from the source, and the trusted NC-Link agent/adaper are utilized to connect the heterogeneous equipments trustedly in the production line. The proposed framework can improve the information security level of the open CNC production line while maintaining its openness. © 2022 IEEE.

关键词： Trusted computing

来源：评论

学校读者我要写书评

暂无评论

Fabric Defect Defection based on Lightweight Convolutional Denoising Auto-Encoder 22

Fabric Defect Defection based on Lightweight Convolutional D...

引用

8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Jin, Dong Li, Wenzheng Sun, Zhigang Li, Xiao School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450396110

In the industrial production environment, the scarcity of defect samples and the high labor cost of labeling defect samples make supervised machine learning models difficult to implement. In addition, defect detection using deep learning models usually requires high computation cost and advanced hardware platform, which is not suitable for running on embedded platforms. To solve this problem, this paper proposes an unsupervised fabric defect detection method based on lightweight convolutional denoising auto-encoder(LCDAE). The LCDAE model is constructed by the bottleneck layer in MobileNetV3. Experimental results show that the method can effectively detect and localize defects with less computation and has the potential to perform defect detection on edge-embedded platforms. © 2022 ACM.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：