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2024 China Automation Congress, CAC 2024

作者： Xie, Junwei Yuan, Meng Xu, Zhezhuang Liu, Chi Xia, Yuxiong College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Fujian Huading Intelligent Manufacturing Technology Co. Ltd. Fuzhou350000 China

ISBN: (纸本)9798350368604

Short-term load forecasting of buildings plays a key role in demand management, however, when dealing with massive data, the prevalent practice of training and testing the system as a whole overlooks pattern variations inside data and potentially limits predictive performance. To address this issue, this paper proposes an ensemble deep random vector functional link (edRVFL) model that combines adaptive ensemble clustering and dynamic weighting strategy for load forecasting of an industrial building. Firstly, the adaptive ensemble clustering that combines ordering points to identify the clustering structure and K nearest neighbor is employed to determine the electricity load usage patterns. Subsequently, the improved particle swarm optimization algorithm is applied to adjust the weights of load curves in different typical day scenarios. Finally, a dynamic weighting strategy is designed to dynamically assign model weights to two clusters, where one matches the type of predicted load pattern for the day being forecasted and another for the cluster of the previous day. The experiment in a real building verifies the effectiveness of the proposed algorithm, which has higher prediction accuracy than other comparison algorithms including one-week interval and different ensemble clustering. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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LPV state-feedback control of a robotic manipulator via LMI optimization

LPV state-feedback control of a robotic manipulator via LMI ...

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XXII International Symposium on information, Communication and Automation Technologies, ICAT

作者： Zoltán Téczely Bálint Kiss Department of Control Engineering and Information Technology Budapest University of Technology and Economics Budapest Hungary

This paper presents an LPV model-based controller synthesis case study on a 2-DOF robotic manipulator. A polytopic LPV formulation was chosen with two scheduling variables. An $\boldsymbol{H}_{\infty}$ control strategy was used for the reference tracking objective which was implemented through LMI optimization and was compared to a nominal $\boldsymbol{H}_{\infty}$ controller and feedback linearization extended with PD reference tracking criterion. The solution was tested on a real-life robotic arm located at BME Robotics Laboratory. Numerical evaluation was based on a joint measure of performance and robustness.

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Consensus Path-Following of Multiple Wheeled Mobile Robots with Complex Dynamics by Adaptive Fixed-Time Fuzzy control

Consensus Path-Following of Multiple Wheeled Mobile Robots ...

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Chinese Intelligent Automation Conference, CIAC 2023

作者： Yang, Junyi Li, Zhichen Yan, Huaicheng Zhang, Hao Xi, Zhenghao School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China Department of Control Science and Engineering Tongji University Shanghai200092 China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China

ISBN: (纸本)9789819961863

This paper concentrated on fixed-time consensus path-following control for multiple wheeled mobile robots(WMRs). The main goal is to achieve fixed-time consensus performance of multiple robot systems in situations where the complex dynamic model of the robot is partially unknown, and the convergence time is independent of the initial states of the system. In order to facilitate implementation, the path-following control is first decoupled into speed control and heading control. By introducing an algebraic implicit reference path, a new path following control method is developed for the robots based on kinematic models. Secondly, by means of fuzzy logic system theory, a time-varying gain adaptive fuzzy control strategy is proposed, which approximates the unknown parts of the dynamic models and compensates for external disturbances in real time. In addition, the fixed-time stability analysis of tracking error dynamics based on backstepping method is presented by constructing a barrier and a quadratic form of Lyapunov function. Finally, its advantages and effectiveness are demonstrated by simulation examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Mobile robots

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of engineering & technology 2023.

关键词： Machine learning

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Reinforcement Learning Behavioral control for Nonlinear Autonomous System

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1561-1573页

作者： Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang the College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian ProvinceFuzhou 350108 G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear *** this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error ***,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission *** with existing mission supervisors,the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural *** the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control *** with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and *** error signals are proved to be semi-globally uniformly ultimately bounded(SGUUB).Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers,respectively.

关键词： Behavioral control mission supervisor nonlinear autonomous system reinforcement learning

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Detecting Credit Card Fraud using Machine Learning

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2021年第24期15卷 108-122页

作者： Almuteer, Arjwan H. Aloufi, Asma A. Alrashidi, Wurud O. Alshobaili, Jowharah F. Ibrahim, Dina M. Department of Information Technology College of Computer Qassim University Buraydah Saudi Arabia Computers and Control Engineering Department Faculty of Engineering Tanta University Tanta Egypt

Credit card is getting increasingly more famous in budgetary exchanges, simultaneously frauds are likewise expanding. In the past, fraud practitioners were identified using rule-based master frameworks, which ignored a variety of variables, including the outlandishly imbalanced nature of positive and negative cases. Using named information, we provide an approach to fraud detection that uses Convolutional Neural Networks (CNNs) and is based on CNNs. An element lattice speaks to a plethora of interchange information and uses a convolutional neural organization to recognize a large number of idle examples for each of those examples. A considerable business bank's boss presentation is compared with several best-in-class techniques in trials on truly monstrous exchanges. Our objective is to combine CNN with LSTM and Auto-encoder to increase credit card fraud detection while improving the previous models' performance. By using these four models;CNN, AE, LSTM, and AE&LSTM. each of these models is trained by different parameter values highest accuracy has been achieved where the AE model has accuracy = 0.99, the CNN model has accuracy = 0.85, the accuracy of the LSTM model is 0.85, and finally, the AE&L-STM model obtained an accuracy of 0.32 by 400 epoch. It is concluded that the AE classifies the best result between these models. © 2021. All Rights Reserved.

关键词： Budget control

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Advances and challenges of methanol-tolerant oxygen reduction reaction electrocatalysts for the direct methanol fuel cell

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Journal of Energy Chemistry 2023年第2期77卷 499-513,I0013页

作者： Muhammad Aizaz Ud Din Muhammad Idrees Sidra Jamil Syed Irfan Ghazanfar Nazir Muhammad Ahmad Mudassir Muhammad Shahrukh Saleem Saima Batool Nanpu Cheng Rahman Saidur School of Materials and Energy Southwest UniversityChongqing 400715China Additive Manufacturing Institute College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060GuangdongChina Chongqing Key Lab for Advanced Materials and Clean Energies of Technologies School of Materials and EnergySouthwest UniversityChongqing 400715China School of Materials Science and Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Department of Chemistry Khawaja Fareed University of Engineering and Information TechnologyRahim Yar Khan 64200Pakistan Laboratory for High Performance Ceramics EmpaSwiss Federal Laboratories for Materials Science and Technology8600 DübendorfSwitzerland Institute for Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina Research Centre for Nano-Materials and Energy Technology School of Engineering and TechnologySunway UniversityBandar SunwayMalaysia Department of Engineering Lancaster UniversityLancasterUnited Kingdom

Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fuel cells must have excellent activity toward oxygen reduction reaction and resistance to methanol oxidation *** review focuses on the methanol tolerant noble metal-based electrocatalysts,including platinum and palladium-based alloys,noble metal–carbon based composites,transition metal-based catalysts,carbon-based metal catalysts,and metal-free *** understanding of the correlation between the activity and the synthesis method,electrolyte environment and stability issues are *** the transition metal-based catalyst,their activity,stability and methanol tolerance in direct methanol fuel cells and comparisons with those of platinum are particularly ***,strategies to enhance the methanol tolerance and hinder the generation of mixed potential in direct methanol fuel cells are also *** review provides a perspective for future developments for the scientist in selecting suitable methanol tolerate catalyst for oxygen reduction reaction and designing high-performance practical direct methanol fuel cells.

关键词： Oxygen reducing reaction Methanol tolerant electrocatalyst Portable power sources Direct methanol Fuel cell

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Tracking Trajectory by Using The Polynomial Method for ACC System Based on Smart Car Platform 17

Tracking Trajectory by Using The Polynomial Method for ACC S...

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17th International Conference on engineering of Modern Electric Systems, EMES 2023

作者： Luu, Duc Lich Hung, Nguyen Viet Lupu, Ciprian University of Science and Technology The University of Danang Faculty of Transportation Mechanical Engineering Da Nang550000 Viet Nam East Asia University of Technology Faculty of Information Technology Bac Ninh Viet Nam University Politehnica of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350310634

A well-known advanced driver assistance technology that can be employed for that is the Adaptive Cruise control System (ACC). Cars equipped with ACC system are to control the car speed to follow a driver's set speed closely when there is no leading car. When a slower leading car is present based on distance sensor, the ACC controlled car are able to keep desired distance with respect to the position and velocity of the car in front. This paper presents a design methodology of Adaptive Cruise control (ACC) system for two smart car platform consist of the leading smart car and a host smart car move on a single lane on a laboratory installation. RST algorithm in the multi algorithms structure is proposed to design in real-time architecture for ACC system. RST algorithm is one of the most effective solutions for the real-time control of nonlinear systems or working regimes. The results of the experiment have been conducted to illustrate the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Adaptive cruise control

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