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automation 5.0: The Key to systems Intelligence and Industry 5.0

IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

automation has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： automation machinery intelligence

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Distributed Time-Varying Optimization with Equality Constraints

Distributed Time-Varying Optimization with Equality Constrai...

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International Conference on control and automation (ICCA)

作者： Zheng Yang Ji Ma Xiang Xu Department of Automation Xiamen University Xiamen Fujian China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, we consider the distributed time-varying optimization problem with coupled equality constraints over a connected undirected network. To address this issue, we design a novel distributed constraint optimization algorithm, and establish its ISS stability with external disturbances and tracking errors as the input and state, respectively. Moreover, the obtained result includes distributed constrained optimization with static objective functions as a special case. In comparison to existing relevant works, the proposed algorithm demonstrates exponential convergence for cases involving static objective functions. Finally, the theoretical results are validated via a numerical example.

关键词： Constraint optimization automation Linear programming Trajectory Optimization Numerical stability Convergence

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Mesh denoising in prosthetics manufacturing applications using average filtering, linear heat diffusion and bilateral filtering 12

Mesh denoising in prosthetics manufacturing applications usi...

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12th Mediterranean Conference on Embedded Computing, MECO 2023

作者： Kaplun, Dmitrii Voznesensky, Alexander Sufelfa, Alisa Gulvanskii, Vyacheslav Brikova, Olga Saint Petersburg Electrotechnical University 'Leti' Department of Automation and Control Processes St. Petersburg Russia Saint Petersburg Electrotechnical University 'Leti' Mobile Information Systems Laboratory St. Petersburg Russia Saint Petersburg Electrotechnical University 'Leti' Fundamental Foundations of Intelligent Systems Laboratory St. Petersburg Russia

ISBN: (纸本)9798350322910

It is important for every person using a prosthesis that the prosthetic socket fits snugly to the extremity stump. The authors propose to improve the preprocessing stage of a three-dimensional scan extremity stump model using denoising. Ten 3D scans were selected for testing. Additive white Gaussian noise was considered. Three denoising algorithms (average filtering, linear heat diffusion, bilateral filtering) were discussed. SNR was calculated before and after denoising. Then the δ-SNR and the δavg-SNR were calculated. The execution time of algorithms with averaging more than 1000 runs was also estimated. Denoising was performed on three-dimensional models obtained by optical scanning of patients with lower limb stumps. The results of the work help solve the pretreatment problem for a stump model to an individual prosthetic socket manufacture. © 2023 IEEE.

关键词： Gaussian noise (electronic)

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Decision Making with Z-Bounded Interval Preference 15th

Decision Making with Z-Bounded Interval Preference

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15th International Conference on Application of Fuzzy systems, Soft Computing and Artificial Intelligence Tools, ICAFS 2022

作者： Alizadeh, Akif V. Aliyev, Rafig R. Department of Electronics and Automation Azerbaijan State Oil and Industry University 20 Azadlig Avenue Baku1010 Azerbaijan Research Laboratory of Intelligent Control and Decision-Making Systems in Industry and Economics Azerbaijan State Oil and Industry University Azadlyg Avenue 20 Baku1010 Azerbaijan

ISBN: (纸本)9783031252518

In many real-world decision problems under uncertainty, information is not exact, and merely lower and upper bounds are available. This leads to dual uncertainties, e.g., both lower and upper bounds are uncertain. In this paper uncertainties in preferences of Decision Makers are expressed as Z-boundary intervals. The lower and upper bounds of an interval can be presented as Z-numbers. Real-world decision making under Z-bounded intervals is provided to demonstrate the effectiveness and feasibility of the proposed approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Multi-attribute Decision Making Under Z-Set Valued Uncertainty 15th

Multi-attribute Decision Making Under Z-Set Valued Uncertain...

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15th International Conference on Application of Fuzzy systems, Soft Computing and Artificial Intelligence Tools, ICAFS 2022

作者： Aliyev, Rafig R. Alizadeh, Akif V. Research Laboratory of Intelligent Control and Decision-Making Systems in Industry and Economics Azerbaijan State Oil and Industry University Azadlyg Avenue 20 Baku1010 Azerbaijan Department of Electronics and Automation Azerbaijan State Oil and Industry University 20 Azadlig Avenue Baku1010 Azerbaijan

ISBN: (纸本)9783031252518

In real-life decision problems it is usually we know the gain (outcome value) corresponding to given set of alternatives with some uncertainty. Instead of numerical value of this outcomes, there is set of possible values of outcomes. In this paper, we consider decision making under Z-set valued uncertainty. In situation when consequences of decision making is Z-set to define a fair price for a participation in such decision to select more appropriate alternatives is investigated. For this in the paper fair price approach is used. A real-word application is considered to demonstrate the usefulness of the proposed approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Reinforcement Learning Applied to Agent Path Planning 41

Reinforcement Learning Applied to Agent Path Planning

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第41届中国控制会议

作者： Fenglan Sun Xiaoshuai Wu Guoxiong Long Key Laboratory of Intelligent Analysis and Decision on Complex Systems School of ScienceChongqing University of Posts and Telecommunications Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of AutomationChongqing University of Posts and Telecommunications Department of Complexity Science Potsdam Institute for Climate Impact Research

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper provides an enhanced Q-learning algorithm for agent path planning in traditional grid maps,which solves the problem of agent path planning in grid *** an unknown environment,the classic Q-learning algorithm addresses the agent's path planning ***,there are several limits to this strategy in terms of path planning:the agent could only move nearby grids,and the step size is only one *** Q-learning algorithm,including changes the agent's direction and step *** action direction of agents is increased from four to *** movement step of agents is raised from one to three *** new method makes the convergence faster and proxy path ***,a set of simulation tests are presented to validate the modified Q-learning algorithm.

关键词： Agent Path planning Q-learning Grid method

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods 32

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Zhou, Yujian She, Jinhua Wang, Feng Iwasaki, Makoto 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 Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan Nagoya Institute of Technology Department of Electrical and Mechanical Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350399714

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method. © 2023 IEEE.

关键词： Disturbance rejection

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Implementation and Application of Solvers for Simulation and Execution of control Algorithms in NCSLab

Implementation and Application of Solvers for Simulation and...

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International Conference on Electronic Engineering and Informatics (EEI)

作者： Jiuzheng Su Zhongcheng Lei Wenshan Hu Guo-Ping Liu Department of Artificial Intelligence and Automation Wuhan University Wuhan China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In order to solve the problems of high dependency and low flexibility caused by calling three-party services during simulation and experiments, this paper uses the NCSLab (Networked control System Laboratory) as an application platform to implement the functions of multiple ordinary differential equation solvers, which are used for real-time simulation and experimentation of control algorithm. This paper mainly integrates the common ordinary differential equation solving methods and NCSLab platform, and verifies the support of NCSLab platform for different solving methods through the actual simulation process.

关键词： Networked control systems Computational modeling Ordinary differential equations Real-time systems Computational efficiency Informatics

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Design of Supervisory Model Predictive control for HVAC systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort

Design of Supervisory Model Predictive Control for HVAC Syst...

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International Conference on control, automation and systems ( ICCAS)

作者： Panithan Srisurapanon David Banjerdpongchai Department of Electrical Engineering Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Chulalongkorn University Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge.

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Partially Occluded Face Expression Recognition with CBAM-Based Residual Network for Teaching Scene

Partially Occluded Face Expression Recognition with CBAM-Bas...

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2023 China automation Congress, CAC 2023

作者： Bai, Yanxing Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcomes the problem of localized occlusion face feature extraction by focusing on the regions and channels containing important information in the occluded face data through CBAM. Multi-task cascaded convolutional networks (MTCNN) are firstly utilized to localize the key regions of face emotion, and then deep emotion features are extracted by CBAM-ResNet network. The final emotion labels are generated. The effectiveness of this paper's method is verified on the RAF-DB dataset and the occluded CK+ dataset. The experimental accuracy in the RAF-DB dataset is 76.3%, which is 3.74% and 1.64% higher than the accuracy produced by the method of RGBT, and the WLS-RF, respectively. Application experiments are carried out in the real teaching scenario, which verifies the applicability of the algorithm in the real teaching scene. © 2023 IEEE.

关键词： Emotion Recognition

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