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Data Driven control and Learning Systems (DDCLS)

作者： Xinze Xi Pengqi Sun Chao Xing Shengnan Li Xincui Tian Electric Power Research Institute of Yunnan Power Grid Co. Ltd. Kunming P. R. China Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology P. R. China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming P. R. China Faculty of Electric Power Engineering Kunming University of Science and Technology P. R. China

An variational mode decomposition (VMD) has been applied in the field of harmonic detection, but the error will be large if the decomposition parameters are set artificially. To improve the accuracy of VMD in inter-harmonics detection, we need to determine the number of wolves, maximum number of iterations, convergence factor and other parameters, and then select component sample entropy function as the fitness function of the Grey Wolf algorithm. The variational mode decomposition can be utilized to extract the harmonic signal and choose a minimum envelope entropy weight as the best component. The Fourier transform is used to obtain the amplitude and frequency information of interharmonic signals. The simulation results show that the proposed method can effectively optimize the parameters and reduce the VMD decomposition error. Compared with empirical mode decomposition (EMD), complementary ensemble empirical mode decomposition (CEEMD) and empirical wavelet transform (EWT), the VMD with optimized parameters can significantly improve the accuracy of interharmonic detection and improve the accurate trace of accident source.

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Tabular Q-learning Based Reinforcement Learning Agent for Autonomous Vehicle Drift Initiation and Stabilization

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IFAC-PapersOnLine 2023年第2期56卷 4896-4903页

作者： Szilárd H. Tóth Ádám Bárdos Zsolt J. Viharos Department of Automotive Technologies Budapest University of Technology and Economics Budapest Hungary Research Laboratory on Engineering and Management Intelligence Intelligent Processes Research Group Institute of Computer Science and Control Centre of Excellence in Production Informatics and Control Eötvös Loránd Research Network (ELKH) Centre of Excellence of the Hungarian Academy of Sciences (MTA) Budapest Hungary Department of Management and Business Law Faculty of Economics John von Neumann University Kecskemét Hungary

This paper aims to report on novel research results about developing a reinforcement learning agent for steady-state vehicle drift motion control. Based on the previous results of this research, the primary goal was to eliminate the problems causing learning instability experienced with the Soft Actor-Critic (SAC) algorithm applying Tabular Q-learning in this work. Trained in a MATLAB/Simulink-based simulation environment, the resulting agent succeeded in this task while being able to smoothly operate the vehicle to achieve and retain the desired target drift state, regardless of the discreet nature of the algorithm used for solving an inherently continuous task.

关键词： Motion control Autonomous Vehicles Vehicle Dynamics control Reinforcement Learning Vehicle Drifting Handling Limits

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A Robotic Framework for the Robot@Factory 4.0 Competition

A Robotic Framework for the Robot@Factory 4.0 Competition

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Ricardo B. Sousa Cláudia D. Rocha João G. Martins João Pedro Costa João Tomás Padrão José Maria Sarmento José Pedro Carvalho Maria S. Lopes Paulo G. Costa António Paulo Moreira Faculty of Engineering University of Porto (FEUP) Porto Portugal CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal University of Trás-os-Montes and Alto Douro (UTAD) Vila Real Portugal C2SR - Cyber-Physical Control Systems and Robotics SYSTEC - Research Center for Systems and Technologies Porto Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese Robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Although the literature has works proposing frameworks for the original version of the Robot@Factory competition, none of them proposes a system framework for the Robot@Factory 4.0 version that presents the hardware, firmware, and software to complete the competition and achieve autonomous navigation. This paper proposes a complete robotic framework for the Robot@Factory 4.0 competition that is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by winning the 2022 and 2023 editions of the competition.

关键词： Technological innovation Education Propulsion Production facilities Software Hardware Autonomous robots

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Hui Guo Di Xie Jiahao Pang Jie He Caixu Xu Xuejian Zhang Minglang Chen Faculty of Arts and Humanities Macao University of Science and Technology Wuzhou China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China college of Electronical and Information Engineering Wuzhou University Wuzhou China

At present, the self-similarity of images has received wide attention in many fields such as image compression. Most of the images have strong self-similarity through the human eye visual system observation. However, the special images with strong self-similarity for human eye observation such as biomicroscopy are not digitally reflected by a certain algorithm, this paper proposes a self-similarity coefficient algorithm that is applicable to special natural images such as biomicroscopy and aerial photography, which has high self-similarity coefficients for biomicroscopy and other images.

关键词： Photography Image coding Microscopy Visual systems Ubiquitous computing Biomedical imaging

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear Systems Against Actuator Faults

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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International Symposium on Autonomous Systems (ISAS)

作者： Shanlin Liu Yingwei Zhang Xudong Zhao Hesheng Wang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of IntelligentControl and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent.

关键词： Actuators Backstepping Fault tolerant systems Process control Artificial neural networks control systems Approximation error

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A New Terminal Sliding Mode control for Bridge Cranes 1

A New Terminal Sliding Mode Control for Bridge Cranes

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1st International Conference on Smart City Challenges and Outcomes for Urban Transformation, SCOUT 2021

作者： Wang, Tianlei Zheng, Zhaoming Chen, Ziyang Zhang, Jingling Xu, Jinzhao Wang, Hongmin Kin, Kenneth Teo Tze Xie, Yongwen Faculty of Intelligent Manufacturing Wuyi University Guangdong Jiangmen529020 China School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China School of Mathematics and Computational Science Wuyi University Guangdong Jiangmen529020 China Faculty of Engineering University Malaysia Sabah Sabah Kota Kinabalu Malaysia Jinming Machinery Manufacturing Co. Ltd Guangdong Jiangmen529020 China

ISBN: (纸本)9781665407670

In different transportation tasks of bridge cranes, the mass of the load and the cable length are different. To solve this problem, this paper designs a model-free adaptive non-singular terminal sliding mode controller. Specifically, the bridge crane model is changed first, and then a suitable non-singular terminal sliding surface is selected. The adaptive rate is introduced in the design of the controller, so that the driving force is continuous and does not require information of system parameters. The Lyapunov theorem proves that the system is stable. Finally, simulation experiments verify the effectiveness of the algorithm proposed in this paper. © 2021 IEEE.

关键词： Sliding mode control

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Performance Investigation of Instantaneous Reactive Power control for 5 Level-Neutral Point Clamped Grid-Connected Photovoltaic Inverter

Performance Investigation of Instantaneous Reactive Power Co...

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Electrical engineering and Automatic control (ICEEAC), International Conference on

作者： Oumaymah Elamri Alla Eddine Toubal Maamar Charaf Chermite Moulay Rachid Douiri Mostefa Kermadi Saad Mekhilef LAMIGEP multidisciplinary research laboratory École Marocaine des Sciences de l'Ingénieur (EMSI) of Marrakech Marrakech Morocco Department of Electrical Systems Engineering Faculty of Technology University of M'hamed Bougara of Boumerdes Boumerdes Algeria Physics Department Control and Computer Science for Intelligent Systems and Green Energy Faculty of Science and Technology Cadi Ayyad University Marrakech Morocco School of Engineering University of Leicester Leicester United Kingdom Power Electronics and Renewable Energy Research Laboratory (PEARL) Kuala Lumpur Malaysia Swinburne University of Technology Hawthorn Vic Australia

ISBN: (数字)9798350349740

ISBN: (纸本)9798350349757

The utilization of solar energy in grid-connected photovoltaic installations has become increasingly significant. This article introduces a photovoltaic system seamlessly integrated with a three-phase network. The system employing a five-level Neutral Point Clamped (NPC) voltage source inverter is designed for a single-step connection to enhance power quality in the distribution network. The control technique employed for the efficient functioning of the photovoltaic system is based on the notion of instantaneous reactive power. Notably, this strategy is straightforward, operates the system throughout the day, and eliminates the need for Phase-Locked Loop (PLL) usage. The Pulse-Width Modulated (PWM) Current controller sends switching signals to the NPC multilevel inverter, which does a great job of dynamic performance under steady-state and transient situations. The proportional-integral controller regulates the voltage of the Uninterruptible Power Supply DC bus capacitors. The proposed system undergoes comprehensive simulation validation under various irradiation levels.

关键词： Photovoltaic systems Reactive power Voltage source inverters Switches Solar energy Steady-state Transient analysis

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Clustering Interval and Triangular Granular Data: Modeling, Execution, and Assessment

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IEEE Transactions on Neural Networks and Learning Systems 2024年第6期36卷 10000-10014页

作者： Yiming Tang Wenbin Wu Witold Pedrycz Jianwei Gao Xianghui Hu Zhaohong Deng Rui Chen Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada School of Computer and Information Hefei University of Technology Hefei China Faculty of Automatic Control Electronics and Computer Science Silesian University of Tecghnology Gliwice Poland Research Center of Performance and Productivity Analysis Istinye University Istanbul TÃrkiye School of Computer Science and Engineering Southeast University Nanjing China School of Artificial Intelligence and Computer Jiangnan University Wuxi Jiangsu China

In current granular clustering algorithms, numeric representatives were selected by users or an ordinary strategy, which seemed simple; meanwhile, weight settings for granular data could not adequately express their structural characteristics. Aiming at these problems, in this study, a new scheme called a granular weighted kernel fuzzy clustering (GWKFC) algorithm is put forward. We propose the representative selection and granularity generation (RSGG) algorithm enlightened by the density peak clustering (DPC) algorithm. We build interval and triangular granular data on the strength of numeric representatives obtained by RSGG under the principle of justifiable granularity (PJG), in which we establish some combinations of functions and boundary constraints and prove their properties. Furthermore, we present a novel distance formula via the kernel function for granular data and design new weights to affect the coverage and specificity of granular data. In addition, based upon these factors, we come up with the GWKFC algorithm of granular clustering, and its performance with different granularity is assessed. To sum up, a macro framework involving granular modeling, granular clustering, and assessment has been set up. Lastly, the GWKFC algorithm and ten other granular clustering algorithms are compared by experiments on some artificial and UCI datasets together with datasets with large data or those of high dimensionality. It is found that the GWKFC algorithm can provide better granular clustering results by contrast with other algorithms. The originality is embodied as follows. First, we improve the previous density radius and present the RSGG algorithm to acquire numeric representatives. Second, we propose a new strategy to determine granular data boundaries and further obtain novel weights enlightened by the idea of volume. Lastly, we employ the kernel function to calculate the distance between granular data, which has a stronger spatial division ability than the pr

关键词： Clustering algorithms Data models Computational modeling Numerical models Kernel Phase change materials Granular computing Uncertainty Fuzzy sets Noise

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A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification

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Plant Diseases and Pests 2024年第2期15卷 9-16页

作者： Mengmeng ZHANG Xiujuan WANG Mengzhen KANG Jing HUA Haoyu WANG Feiyue WANG State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning *** demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model ***,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial *** issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data *** address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.

关键词： Rice disease and pest identification Convolutional neural networks Distributed training Federated learning(FL) Open-source data sharing platform

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Sensitivity Analysis and Calibration for a Two-Dimensional State-Space Model of Metal Hydride Storage Tanks Based on Experimental Data

SSRN

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SSRN 2024年

作者： Chen, Mingrui Batlle, Carles Escachx, Bryan Costa-Castelló, Ramon Na, Jing Institut de Robòtica i Informàtica Industrial CSIC-UPC. C/ Llorens i Artigas 4-6 Barcelona08028 Spain Departament de Matemàtiques Institut d’Organització i Control EPSEVG UPC Vilanova i la Geltru08800 Spain Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China

In this paper, a state-space model of the metal hydride tank is formulated and analyzed in detail. Firstly, we simplify a three-dimensional state-space model of the metal hydride tank by adding temperature sensors to deal with the influence of the external environment. Secondly, an improved method using a pipe model is proposed, which takes the pipe pressure as the system input and the mass flow rate as the system output. The proposed model solves the problem that the conventional metal hydride tank models usually take the mass flow rate as input and ignore the pressure as system input in industrial scenarios. Thirdly, the First-order Trajectory Sensitivity Analysis (FOTSA) method is adopted to determine the sensitivity of selected unknown parameters. Finally, the Particle Swarm Optimisation (PSO) algorithm is used to estimate the unknown model parameters based on the results of the sensitivity analysis. A comparison between experimental data and simulation results demonstrates that the proposed model reflects the dynamic characteristics of metal hydride tanks very well. © 2024, The Authors. All rights reserved.

关键词： Sensitivity analysis

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