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Indirect adaptive observer control (I-AOC) design for truck–trailer model based on T–S fuzzy system with unknown nonlinear function

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Complex and Intelligent Systems 2024年第5期10卷 7311-7331页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Chang, Wer-Jer Yahya, Abid Badruddin, Irfan Anjum Kamangar, Sarfaraz Hussien, Mohamed Artificial Intelligence Research Institute China University of Mining and Technology Department of Automation University of Science and Technology of China Department of Marine Engineering of National Taiwan Ocean University (NTOU) Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Department of Mechanical Engineering College of Engineering King Khalid University Department of Chemistry Faculty of Science King Khalid University

Tracking is a crucial problem for nonlinear systems as it ensures stability and enables the system to accurately follow a desired reference signal. Using Takagi–Sugeno (T–S) fuzzy models, this paper addresses the problem of fuzzy observer and control design for a class of nonlinear systems. The Takagi–Sugeno (T–S) fuzzy models can represent nonlinear systems because it is a universal approximation. Firstly, the T–S fuzzy modeling is applied to get the dynamics of an observational system in order to estimate the unmeasurable states of an unknown nonlinear system. There are various kinds of nonlinear systems that can be modeled using T–S fuzzy systems by combining the input state variables linearly. Secondly, the T–S fuzzy systems can handle unknown states as well as parameters known to the indirect adaptive fuzzy observer. A simple feedback method is used to implement the proposed controller. As a result, the feedback linearization method allows for solving the singularity problem without using any additional algorithms. A fuzzy model representation of the observation system comprises parameters and a feedback gain. The Lyapunov function and Lipschitz conditions are used in constructing the adaptive law. This method is then illustrated by an illustrative example to prove its effectiveness with different kinds of nonlinear functions. A well-designed controller is effective and its performance index minimizes network utilization—this factor is particularly significant when applied to wireless communication systems. © The Author(s) 2024.

关键词： Adaptive observer control Feedback control design Indirect method Lyapunov–Krasovskii candidate T–S fuzzy models

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Data-Driven Group Formation Control of Cyber-Physical Systems via Distributed Cloud Computing

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 341-350页

作者： Ren, Hongru Long, Yinren Li, Hongyi Huang, Tingwen Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper investigates the group formation control problem for cyber-physical systems (CPSs) with random communication constraints. The distributed cloud computing system is constructed to divide agents into groups and establish communication between agents. A data-driven predictive control strategy is proposed by combining networked predictive control and model-free adaptive control method. The desired group formation control performance can be achieved and the three-channel random communication constraints of CPSs are actively compensated. Thisstrategy does not require the system model and relies solely on the system's I/O data for adaptive learning. Further analyses concludes the conditions for simultaneous reach stability and group formation of the closed-loop CPSs using the data-driven predictive control strategy. The effectiveness of the proposed strategy is validated by simulation results. © 2023 IEEE.

关键词： Distributed cloud

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A Novel Approach with Fusion Edge Prediction Strategy for Table Structure Recognition 11

A Novel Approach with Fusion Edge Prediction Strategy for Ta...

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11th International Conference on Information Systems and Computing Technology, ISCTech 2023

作者： Liu, Yingli Zhang, Guangtao Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

Table, as an information carrier with high information density and direct display form, are widely used in scientific literature and social production documents. Accurately identifying tables from various documents will significantly promote the intelligent application of documents. The table's structural information is crucial for comprehending how the text content in the table relates to one another, but teaching a computer to fully understand a table's structure is still a very difficult undertaking. In this research work, we provided a unique edge-based method to recognize table structures. Specifically, we define the inter-cell relationships as an edge prediction problem and leverage graph convolutional networks to learn representations of the cells. These learned representations are then utilized to directly predict the connections between the cells. The experimental results conducted on three publicly available datasets for table structure recognition provide compelling evidence supporting the feasibility and usefulness of our presented methodology. © 2023 IEEE.

关键词： Forecasting

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Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 75-89页

作者： Aijuan Song Guohua Wu Witold Pedrycz Ling Wang School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland Department of Automation Tsinghua UniversityBeijing 100084China

Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple *** algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one ***,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used *** contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve *** VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation *** enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the *** test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,*** results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared ***,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.

关键词： Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)

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Multi-objective performance prediction based on a self-constructed Al-Si alloy dataset 11

Multi-objective performance prediction based on a self-const...

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11th International Conference on Information Systems and Computing Technology, ISCTech 2023

作者： Hu, Dan Liu, Yingli Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

The combination of data-driven approaches and machine learning techniques has changed the design approach for new materials, propelling materials science research into the realm of the fourth paradigm. Researchers in the field of materials science have increasingly focused on utilizing machine learning methods to uncover the underlying nonlinear relationships within material data. However, there is currently limited research in the field of aluminum-silicon alloys regarding the prediction of alloy performance based on the composition-process-structure relationship. Additionally, there is a lack of data sharing in the aluminum-silicon alloy domain. Therefore, this study proposes a methodology. Firstly, an aluminum-silicon alloy dataset is constructed by mining relevant information from materials literature. Then, high-dimensional features in the dataset are subjected to feature selection techniques for dimensionality reduction. Subsequently, a multilayer perceptron model is applied to investigate the relationship between input features such as alloy composition, preparation process, and microstructural parameters, and output features such as yield strength, ultimate tensile strength, and elongation, enabling performance prediction. © 2023 IEEE.

关键词： Feature Selection

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Computational-Heuristic Algorithm for Tomographic Solution of Industrial Flaw Detection Problems

Computational-Heuristic Algorithm for Tomographic Solution o...

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International Conference on Actual Problems of Electronic Instrument engineering (APEIE)

作者： Alexander V. Peshkov Sergey M. Zerkal Faculty of Automation and Computer Engineering Novosibirsk State Technical University Novosibirsk Russia

This paper presents the results of the development and study of the application of a computational heuristic algorithm for industrial tomography based on the use of a reference sample of an industrial product. Thus, based on a priori information about the reference sample of the product, it is possible to build a local tomographic reconstruction from limited initial data due to the selective sensitivity of the object under study to probing radiation. This approach is consistent with the principle of "strong methods", which has recently proven itself well in the field of artificial intelligence. The results obtained form the basis for the development of an appropriate information and computing technology, including algorithmic and software for computer processing and interpretation of measurement data. The paper also presents the designed architecture and software prototype with a graphical interface that implements local tomographic reconstruction based on the proposed algorithms. The presented experimental results testify to the efficiency and speed of the proposed algorithm in comparison with the classical algorithm of computed tomography. The proposed algorithm also makes it possible to detect defects of small thickness, when the classical tomography algorithm cannot cope. From an applied point of view, this study is of interest in the heuristic search for a defect in a product model and allows us to conclude that it is promising in the field of industrial flaw detection.

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Small-Signal and Transient Stability Investigation of Inverter Grid Synchronization

Small-Signal and Transient Stability Investigation of Invert...

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Circuits, Systems, Communications and computers (CSCC), International Conference on

作者： Alexander Schöley Torsten Jeinsch Faculty of Computer Science and Electrical Engineering University of Rostock Institute of Automation Germany

Grid synchronisation is essential for grid following inverter control. Typically, a phase-locked loop (PLL) is used to perform the synchronisation, but it is known that the PLL can fail to synchronise with the grid in weak grid scenarios. Although there have been many studies on this topic which relate the grid impedance, the grid voltage and the PLL parameterisation to the grid synchronisation, comprehensive analyses are difficult due to the nonlinear nature of the underlying system. Therefore, the exact relationships remain unclear. This paper investigates the stability of PLL-based grid synchronisation for a grid-side inverter with LC-type output filter and RL-type grid impedance. An analytical steady-state solution is presented, which is used for linearization and evaluation of the small-signal stability. Additionally, the transient stability with consideration of nonlinearities is investigated and a condition for stability of the PLL-based grid synchronization in the transient case is derived. The results are validated by numerical simulations.

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Formation Control of Heterogeneous Multi-Agent Systems Under Fixed and Switching Hierarchies

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IEEE Access 2024年 12卷 97868-97882页

作者： Shamrooz Aslam, Muhammad Bilal, Hazrat Chang, Wen-Jer Yahya, Abid Anjum Badruddin, Irfan Kamangar, Sarfaraz Hussien, Mohamed China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou221116 China University of Science and Technology of China Department of Automation Hefei230026 China Department of Marine Engineering Keelung202 Taiwan Botswana International University of Science and Technology Department of Electrical Computer and Telecommunications Engineering Palapye Botswana King Khalid University College of Engineering Department of Mechanical Engineering Abha Saudi Arabia King Khalid University Faculty of Science Department of Chemistry Abha61413 Saudi Arabia

Modern information technology is driving the rapid development of the information and automation industry through the combination of computer technology, communication technology, and control technology. Inspired by nature's cluster movement, such as birds, people proposed the concept of Multi-Agent Systems (MASs). This paper deals with the formation control problem for a class of heterogeneous multi-agent systems with time-delays. First, the formation control of heterogeneous multi-agent systems with communication delay in fixed and switching topologies is investigated. A heterogeneous multi-agent system model with input delay and communication delay is established. Furthermore, based on this model, the formation control protocol is designed and the stability of the proposed control protocol in fixed and switched topologies is analyzed. The first- and second-order multi-agent control system was formulated for both fixed and switched topology, respectively. Then, using the new LMI toolbox, the feasibility of the parameters is obtained and the example is created by MATLAB. The simulation results show that the proposed formation control protocol with delay in this paper can make the systems converge to the expected value under fixed and switched hierarchies. © 2013 IEEE.

关键词： Topology

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Pain Points in the Experiences of Diabetes Patients with Ambulatory Care. An Analysis of Patients Fears and Recommendations for Service Improvement in Romania 7th

Pain Points in the Experiences of Diabetes Patients with Amb...

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7th International Conference on Advancements of Medicine and Health Care through Technology, MEDITECH 2020

作者： Cotiu, Madalina-Alexandra Constantinescu-Dobra, Anca Sabou, Adrian Faculty of Electrical Engineering Technical University of Cluj-Napoca Cluj-Napoca Romania Faculty of Automation and Computer Science Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (纸本)9783030935634

Diabetes is a chronic metabolic disease with complex management where treatment adherence is crucial for positive outcomes. Research indicates patient satisfaction is associated with patients’ propensity to follow medical recommendations and better treatment adherence. The paper investigated the main fears patients have when accessing medical care for diabetes in an ambulatory setting, as well as their suggestions for service improvement. This was done to contribute to a better understanding of patients’ perceptions regarding the medical care they receive, and the pain points they have in this regard. Healing pain points can lead to higher patient satisfaction. A questionnaire comprising two open questions regarding patients’ fears and suggestions for improvement was distributed in Romania. Demographic, medical, and attitudinal patient data were also collected. The study sample size was 324 respondents. Text analysis and crosstabulation were performed. Results indicated patients most feared a worsening condition and waiting times. Suggested improvements focused on reducing waiting times, increased access to resources, and better clinic facilities. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Patient treatment

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Feasibility of Spine Segmentation in ML-Based Recognition of Vertebrae in X-Ray Images

Feasibility of Spine Segmentation in ML-Based Recognition of...

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International Conference on Actual Problems of Electronic Instrument engineering (APEIE)

作者： Maxim A. Bakaev Denis A. Kobzev Dmitry K. Piletskii Alexander A. Yakimenko Alexander V. Gladkov Faculty of Automation and Computer Engineering Novosibirsk State Technical University Novosibirsk Russia

Medicine remains one of the data-scarce domains, with typical datasets size not exceeding hundreds of thousands items. Correspondingly, straightforward application of end-to-end Deep Learning (ML) methods for Medical Imaging is often problematic. Carefully constructed pipelines that involve filter-based enhancement of raw images allow better outcome and leave more room for feasible data augmentation. In our paper, we explore and develop computer Vision approaches for vertebrae recognition on a limited dataset of X-ray images of human spine. In particular, we test several pre-processing filters, of which Adaptive Histogram Equalization demonstrates the highest accuracy of 85.8% in a naïve model using the popular U-Net architecture. Further, we put forward the mechanism for the automated spine area cropping based on brightness cut-off. This additional step in the pipeline allowed improving the accuracy to 89.9%, which is comparable with the accuracy obtained for MRI images of higher quality. We plan to further increase the prediction quality of the model via spine segmentation into about 20 individual vertebrae and 8-fold data augmentation. The ultimate goal is improving the identification of the vertebrae corners, which currently has the relative error of 4.36%. Our intermediate results reported in the current paper might be of interest to ML engineers who pick the steps for X-ray spine images processing pipelines.

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