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IEEE Conference on Decision and control

作者： Robert Maniarski Wojciech Paszke Hongfeng Tao Eric Rogers Institute of Automation Electronic and Electrical Engineering University of Zielona Góra ul. Szafrana 2 Zielona Góra Poland Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi China School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper develops an iterative learning control law for a class of nonlinear systems. The approach used to represent the nonlinear system dynamics is a Takagi-Sugeno fuzzy repetitive process that considers the two directions of information propagation. Then, the control action investigated is a state feedback control law combined with a PD-type feed-forward learning control law. Consequently, linear matrix inequality techniques can be used for control design. Furthermore, this approach allows the design of control action to satisfy the requirements on both the error convergence and the transient dynamics. Finally, an example demonstrates the properties of the new design.

关键词： State feedback control design Takagi-Sugeno model Nonlinear dynamical systems Linear matrix inequalities Transient analysis Iterative learning control Convergence

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Distributed Optimization by Network Flows with Spatio-Temporal Compression

arXiv

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arXiv 2024年

作者： Ren, Zihao Wang, Lei Yi, Xinlei Wang, Xi Yuan, Deming Yang, Tao Wu, Zhengguang Shi, Guodong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China College of Electronics and Information Engineering Tongji University China School of Electrical Engineering Telecommunications University of New South Wales Sydney Australia School of Automation Nanjing University of Science and Technology China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University China Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2006 Australia

Several data compressors have been proposed in distributed optimization frameworks of network systems to reduce communication overhead in large-scale applications. In this paper, we demonstrate that effective information compression may occur over time or space during sequences of node communications in distributed algorithms, leading to the concept of spatio-temporal compressors. This abstraction classifies existing compressors as spatio-temporal compressors, with their effectiveness described by constructive stability criteria from nonlinear system theory. Subsequently, we apply these spatio-temporal compressors to standard continuous-time consensus flows and distributed prime-dual flows, establishing conditions ensuring convergence. Additionally, we introduce a novel observer-based distributed primal-dual continuous flow integrated with spatio-temporal compressors, which provides broader convergence conditions. These continuous flows achieve exponential convergence to the global optimum when the objective function is strongly convex and can be discretized using Euler approximations. Finally, numerical simulations illustrate the versatility of the proposed spatio-temporal compressors and verify the convergence of algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Stability criteria

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Quantized Distributed Nonconvex Optimization Algorithms with Linear Convergence under the Polyak–Lojasiewicz Condition

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IEEE Transactions on Automatic control 2025年

作者： Xu, Lei Yi, Xinlei Sun, Jiayue Shi, Yang Johansson, Karl H. Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 2Y2 Canada Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai201804 China KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden

This paper considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To reduce the required communication capacity, we introduce an encoder–decoder scheme. By integrating it with distributed gradient tracking and proportional integral algorithms, respectively, we then propose two quantized distributed nonconvex optimization algorithms. Assuming the global cost function satisfies the Polyak–Lojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that our proposed algorithms linearly converge to a global optimal point. Moreover, we show that a low data rate is sufficient to guarantee linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical examples. © 1963-2012 IEEE.

关键词： Cost functions

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Finite-time asynchronous dissipative filtering of conic-type nonlinear Markov jump systems

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Science China(Information Sciences) 2021年第5期64卷 151-162页

作者： Xiang ZHANG Shuping HE Vladimir STOJANOVIC Xiaoli LUAN Fei LIU Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Department of Automatic Control Robotics and Fluid Technique Faculty of Mechanical and Civil EngineeringUniversity of Kragujevac Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University

In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.

关键词： dissipative filtering hidden Markov model finite-time boundedness Markov jump systems conic-type nonlinearity

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Automatic decision-making system for the desalinization of water for irrigation 1

Automatic decision-making system for the desalinization of w...

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1st International Conference on Energetics, Civil and Agricultural Engineering, ICECAE 2020

作者： Gaziyeva, R. Ozodov, E. Bozorov, E. Nigmatov, A. Department of Automation and Control of Technology Process Tashkent Institute of Irrigation and Agricultural Mechanization Engineers 39 Koriy-Niyoziy Tashkent100000 Uzbekistan

The high salinity of water negatively affects soil fertility up to yield loss. In regions with high salinity, unorthodox methods and devices are used to lower the level of mineralization. This article discusses the use of an automatic decision-making system for a device to lower the level of mineralization by diffusion mixing. Construction able to filter water to irrigation rates up to 3 grams per liter and extent the operating period of reverse osmosis. The article provides a detailed description algorithm of a program for automatic control of the water purification process based on the Atmega 328 processor. © Published under licence by IOP Publishing Ltd.

关键词： Mineralogy

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Automated machine learning-assisted enhanced product carbon footprint tracking and analysis in refinery industry: A graph-based life cycle assessment framework

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Journal of Cleaner Production 2025年 514卷

作者： Zhang, Tingwei Peng, Xin Zhong, Weimin Shen, Feifei Ding, Jinliang State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai200237 China State Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai200237 China School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Huzhou Institute of Industrial Control Technology Huzhou313099 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Liaoning Shenyang110819 China

Product carbon footprint assessment and tracking in the refinery industry mainly rely on the expertise of carbon management professionals, which leads to high service costs and involves significant manual intervention, reducing the accuracy of carbon footprint analysis. Accordingly, a data-driven automated product carbon footprint analysis framework based on life cycle assessment is developed in this work. Specifically, an integrated material-energy-carbon multi-scale emission accounting model is established to quantify CO2 emissions accurately. Subsequently, considering that traditional carbon emission allocation methods are generally based on fixed assumptions or simplified proportional relationships, which fail to fully account for the dynamic variations in complex production processes, the allocation results lack accuracy and reliability. Additionally, these methods lack sufficient flexibility and are unable to effectively adjust to the actual carbon emission characteristics of different production stages and products. A data-driven contribution-based carbon emission allocation method is proposed from the carbon flow supply–demand balance perspective to improve allocation transparency. Moreover, a graph-based automated recognition framework of product carbon footprint chains is developed to achieve process operation automation and eliminate manual operations. The proposed models and methods are applied to a real refinery production site for a case study. The results show that the developed product carbon footprint analysis framework can highlight high-energy consumption and high-emission links in the production process and pay more attention to the environmental costs of high-value products. Moreover, CO2 can act as a carbon flow regulation hub, effectively managing emissions through the balance of carbon flow supply and demand. Light oil has a higher contribution rate to CO2 emissions than heavy oil. The carbon footprint of petroleum coke is 3.8677 tCO2eq/t, ma

关键词： Carbon footprint

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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

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IEEE Transactions on control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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Integrating network pharmacology, metabolomics, and gut microbiota analysis to explore the effects of Jinhong tablets on chronic superficial gastritis

arXiv

引用

arXiv 2025年

作者： Xiao, Lihao Zhang, Tingyu Liu, Yun Sutcharitchan, Chayanis Liu, Qingyuan Fan, Xiaoxue Feng, Jian Gao, Huifang Zhang, Tong Li, Shao Institute for TCM-X Department of Automation Tsinghua University Beijing100084 China School of Pharmacy Shanghai University of Traditional Chinese Medicine Shanghai201203 China State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Jiangsu Kanion Pharmaceutical Co.Ltd. Jiangsu Nanjing210000 China

Background: Chronic gastritis (CG) significantly impacts patients' quality of life and can progress to more severe gastric conditions. In China, Traditional Chinese Medicine (TCM) has been widely applied for its holistic efficacy in treating chronic superficial gastritis (CSG), including formulas like Jinhong Tablets (JHT), known for their anti-inflammatory effects. However, the mechanism of action of JHT in treating CSG still require further clarification. Purpose: This study aimed to elucidate the mechanism by which JHT alleviates CSG, integrating network pharmacology, untargeted metabolomics, and gut microbiota analyses. Methods: The CSG rat model was established, and treatment effects were assessed via Hematoxylin and eosin (H&E) staining. Target profiles of JHT’s components and holistic targets of JHT were obtained. Enrichment analyses were performed on holistic targets and a multi-layer biomolecular network of JHT was established. The study also analyzed rat plasma for differential metabolites through untargeted metabolomics and evaluated the diversity and composition of gut microbiota in fecal and cecal contents samples using 16S rRNA sequencing. Results: JHT effectively reduced gastric inflammation in CSG rats. Network pharmacology indicated that diverse metabolic processes including lipid metabolism and nitric oxide metabolism play pivotal roles in the therapeutic effects of JHT on CSG. Metabolomics analysis identified differential metabolites including betaine helping enrich gut microbiota, phospholipids and citrulline indicating the severity of CSG. The pathway enrichment of differential metabolites validated the results of network pharmacology and suggested that the mechanism of action was associated with the gut microbiota. Through gut microbiota analyses, it was discovered that JHT could augment the gut microbiota by enhancing the abundance of betaine. Additionally, JHT was shown to boost the production of short-chain fatty acid (SCFA) by increasing th

关键词： Metabolites

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The Research on Sheet Metal Part Recognition Technology Based on Improved Mask R-CNN

The Research on Sheet Metal Part Recognition Technology Base...

引用

Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Mingfei Liu Jun Liu Kecheng Zhou Jian Wang Key Laboratory of Industrial Intelligence Technology on Chemical Process School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang Liaoning Province China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

The visual recognition of sheet metal parts is a crucial component of industrial automation sorting, particularly under complex lighting and background interference conditions. To enhance the accuracy of sheet metal part recognition, this paper curates a dataset of sheet metal parts acquired by an intelligent light field image sensor and proposes a visual recognition model, PA-CBAM, based on an improved Mask R-CNN. By improving the original feature pyramid FPN and introducing the Convolutional Block Attention Module (CBAM), the model enhances multi-scale feature fusion and the focus on key features: (1) Bottom up paths and shortcut connections have been added between different layers of the traditional FPN feature pyramid, thereby improving multi-scale object detection capability. (2) CBAM further optimizes the model's channel and spatial attention mechanisms, effectively enhancing the capture of edge details and the suppression of background noise. Experimental results show that the proposed PA-CBAM model significantly improves detection and segmentation performance compared to traditional methods, particularly in terms of edge recognition accuracy for sheet metal parts under complex lighting conditions.

关键词： Visualization Accuracy Image edge detection Metals Lighting Object detection Feature extraction Light fields Optimization Sorting

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Dynamic Integral Sliding Mode for Vehicle Platoon control with Constant Time Headway Policy

Dynamic Integral Sliding Mode for Vehicle Platoon Control wi...

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IEEE International Conference on Robotics and Biomimetics

作者： Yanbo Wang Chenglin Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (纸本)9781665405362

This article presents a coupled dynamic integral sliding mode control (DISMC) strategy for a vehicle platoon that consists of a leader and multiple followers subjected to external unknown disturbance. This strategy is designed based on a integral sliding mode control (ISMC) with coupled sliding surface (CSS) under constant time headway (CTH) and bidirectional (BD) information flow topology, so it can alleviate the chattering caused by the control input with sign function. Then, the DISMC is designed to eliminate the chattering problem of the traditional coupled ISMC. In addition, the vehicle stability and the string stability is analyzed strictly. Finally, the numerical simulations are shown to verify the effectiveness and advantages of the proposed strategy.

关键词： Conferences Numerical simulation Stability analysis Topology Safety Vehicle dynamics Numerical stability

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