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Prescribed Performance Control of Two-Time-Scale Systems and Its Application

International Journal of Robust and Nonlinear Control 2025年

作者： Zeng, Ze-Hong Wang, Yan-Wu Liu, Xiao-Kang Yang, Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan China School of Electrical Engineering Guangxi University Nanning China

This article explores the prescribed performance control design for linear two-time-scale systems (TTSSs). Due to ill-conditioning and high dimensionality, existing prescribed performance control methods for single-time-scale systems are unsuitable for TTSSs. Moreover, current TTSS methodologies focus on steady-state performance, often neglecting transient dynamics. To address these challenges, we first apply the Chang transformation to decouple the fast and slow states. Next, we use a state transformation to convert the state equation into block form to eliminate the requirement of a full row-rank input matrix. Finally, the backstepping method is utilized to design the prescribed performance control. The effectiveness and advantages of the proposed control strategy are demonstrated through two examples: a numerical simulation and a hardware-in-the-loop experiment involving an electronic circuit system. © 2025 John Wiley & Sons Ltd.

关键词： backstepping control prescribed performance control two-time-scale system underactuated system

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Spread-based elite opposite swarm optimizer for large scale optimization

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Cognitive Robotics 2022年 2卷 112-118页

作者： Zhang, Li Tan, Yu Guangxi Key Laboratory of Images and Graphics Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

To prevent the traditional particle swarm optimizer (PSO) from inefficient search in complex problem spaces, this paper presents a novel spread-based elite opposite swarm optimizer (SEOSO) for large scale optimization. Inspired by the dandelion seeds in nature, the seeds can randomly spread by wind and grow better for the next generation. To achieve this, the spread learning and elite opposite learning are introduced in SEOSO. In spread learning, the particles are divided into some subswarms and these subswarms can exchange the particles to get more useful information that improves the diversity of the swarm. In elite opposite learning, the opposite position of the particle is used to exclude the worse direction. The experiments are conducted on 35 benchmark functions to evaluate the performance of SEOSO in comparison with several state-of-the-art algorithms. The comparative results show the effectiveness of SEOSO in solving large scale optimization problems. © 2022

关键词： Particle swarm optimization (PSO)

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Research on feature classification method of network text data based on association rules

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International Journal of Computers and Applications 2020年第2期42卷 157-163页

作者： Huang, Hongben Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Wuzhou China

Due to the large number of features, sparse data, low precision of feature extraction, and long time-consuming. Using the current method to classify the text data features, it is difficult to achieve better results. A method of feature classification of network text data based on association rules is proposed. A single word is used as a classification feature to extract the association feature item of text data. The feature item after dimension reduction is to construct classifier. Through the support vector machine algorithm, the network text data feature classification is realized. The highest precision ratio of Hangxia et al.’s study [Hangxia Z, Jiajun Y, Huan R. Text categorization based on deep belief network. Comput Eng Sci. 2016;38(5):871–876] is 69%, the highest precision ratio of Wenjuan et al.’s study [Wenjuan S, Shun L, Fei Y. Iterative text classification framework based on background learning. Comput Eng Applic. 2015;51(9):129–134] is 85%, and the highest precision ratio of the proposed method is 93%. The precision of this method is higher, which shows that the method can accurately reflect the feature class information of text data and reduce the error rate of text classification. Experimental results show that the proposed method can improve the accuracy of classification results and has high robustness. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Association rules

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Comparison of Several Color Histogram Based Retrieval Algorithms

Comparison of Several Color Histogram Based Retrieval Algori...

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2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2016)

作者： Qiuxiang Liao Wuzhou University Guangxi Colleges and University Key Laboratory of Image Processing and Intelligent Information System

ISBN: (纸本)9781509001668

As an important visual characteristic,color has been widely applied in content based image *** paper adopted the RGB color model,wherein intersection distance method,Euclidean distance method and correlation distance method based on color histogram characteristics were applied respectively in the experiments of the same sample image and the same image *** results show that the three algorithms could retrieve the sample image accurately,wherein the histogram intersection algorithm completed the retrieval most quickly;the Euclidean distance method based on simple theories can be understood easily;and the correlation distance method had the lowest recall *** experimental results have certain guidance and reference values for selecting and optimizing the content based image retrieval algorithm.

关键词： accumulative histogram histogram intersection distance euclidean distance correlation distance

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Research summary of "Camellia oleifera fruit picking robot" technical analysis

Research summary of "Camellia oleifera fruit picking robot" ...

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2021 International Conference on Signal processing and Communication Technology, SPCT 2021

作者： Wang, Liang Hou, Yifeng Wang, Kuikui Wei, Chunming Guangxi Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Wuzhou Guangxi543003 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

Aiming at the problems of my country's current camellia fruit picking mainly relying on manual picking, large labor and low efficiency, the development and promotion of camellia fruit picking equipment and technology are discussed, and technical analysis is carried out for the design of camellia fruit picking robots. This article analyzes the characteristics and existing problems of camellia fruit picking, and analyzes the four major components of the picking robot: "end effector", "manipulator motion control system", "visual recognition positioning system"and "driving walking device". In summary, summarize the problems that have been solved, the results achieved, and the difficulties that still exist, so as to provide enlightenment for the subsequent exploration of the subject research of "camellia fruit picking robot". © 2022 SPIE.

关键词： Fruits

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A Novel Self-Learning Network Integrating Contrastive Learning, Perceptual Learning and Masked image Modelling 15

A Novel Self-Learning Network Integrating Contrastive Learni...

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15th International Conference on graphics and image processing, ICGIP 2023

作者： Chen, Yingxian Yang, Rui Lan, Rushi Guangxi Key Laboratory Image and Graphic Intelligent Processing Guilin University of Electronic Technology China

ISBN: (纸本)9781510675018

Unsupervised learning methods in computer vision have achieved remarkable success, exceeding the performance of supervised learning methods. It is noteworthy that current unsupervised learning methods share certain similarities, particularly in their data augmentation techniques. Masking, a type of data augmentation, can be utilized for both contrastive learning and masked image modelling. This paper presents a novel deep learning approach on visual unsupervised learning. It integrates previous methods such as contrastive learning, perceptual learning, self-distillation and masked image modelling. In our method, we treat the network that handles the original images as the teacher network, and the network that handles the masked images as the student network. The student network employs the representations extracted by the projection head for contrastive learning, while the features generated by the decoder are employed for masked image modeling. The process of self-knowledge distillation is facilitated by perceptual learning between the teacher and student networks. This model aligns with the main idea of contrastive learning, which aims to pull similar images closer while pushing dissimilar images further apart. Simultaneously, it reflects the main idea of masked image modelling, which enables the extraction of semantic information from large scale masked pixel reconstruction tasks. Additionally, we compare the effect of self-supervised methods to the performance of the model. Our results show that with only 75 epochs of fine-tuning, our 29M-parameter model achieves 78.5% top-1 accuracy on the imageNet-1k dataset. © 2024 SPIE. All rights reserved.

关键词： Unsupervised learning

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Zhuang Characteristic Culture Detection Based on Improved YOLOV3-SPP Network 14th

Zhuang Characteristic Culture Detection Based on Improved YO...

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14th International Conference on Genetic and Evolutionary Computing, ICGEC 2021

作者： Guo, Shu Qiang, Baohua Xie, Wu Zhai, Yijie Chen, Ruidong Zheng, Hong Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guangxi Guilin541004 China

ISBN: (纸本)9789811684296

In order to enhance the dissemination power of Zhuang culture and enhance the influence of traditional Chinese culture, this article proposes a data set containing the characteristic cultural products of the Zhuang nationality for the unique cultural development of the Zhuang nationality. The data set has a total of 1890 images and contains three categories, namely Zhuang Five-color glutinous rice, Zhuang Bronze drum, and Zhuang Hydrangea. At the same time, the YOLOV3-SPP network based on the darknet53 model is improved, and the ResNet101 structure is introduced to improve the robustness of the network. The verification results on the Zhuang characteristic data set show that the improved YOLOV3-SPP network has an accuracy rate of 92.78% on the Zhuang characteristic data set, which is 1.28% higher than the original YOLOV3-SPP network. The experimental results show that the improved YOLOV3-SPP structure can better realize the detection of the characteristic culture of the Zhuang nationality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： YOLOV3-SPP model Zhuang characteristic data set Zhuang culture

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Semi-Supervised Classification of Data Streams by BIRCH Ensemble and Local Structure Mapping

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Journal of Computer Science & Technology 2020年第2期35卷 295-304页

作者： Yi-Min Wen Shuai Liu Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin 541004China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin 541004China

Many researchers have applied clustering to handle semi-supervised classification of data streams with concept ***,the generalization ability for each specific concept cannot be steadily improved,and the concept drift detection method without considering the local structural information of data cannot accurately detect concept *** paper proposes to solve these problems by BIRCH(Balanced Iterative Reducing and Clustering Using Hierarchies)ensemble and local structure *** local structure mapping strategy is utilized to compute local similarity around each sample and combined with semi-supervised Bayesian method to perform concept *** a recurrent concept is detected,a historical BIRCH ensemble classifier is selected to be incrementally updated;otherwise a new BIRCH ensemble classifier is constructed and added into the classifier *** extensive experiments on several synthetic and real datasets demonstrate the advantage of the proposed algorithm.

关键词： semi-supervised classification clustering data stream concept drift

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Application of intelligent Schedule Management in Volunteer Service System 1

Application of Intelligent Schedule Management in Volunteer ...

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1st IEEE International Conference on Data Intelligence and Innovative Application, DIIA 2024

作者： Li, Yongxin Luo, Xiaonan Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798331504434

As the demand for volunteer services grows, enhancing the efficiency and management of these services has become a key issue. This paper explores methods of integrating intelligent scheduling management functions with volunteer service systems to optimize volunteer time management and task allocation. By analyzing existing volunteer service systems, we propose a novel system framework that integrates intelligent scheduling management. This framework updates volunteer schedules in real- time, automatically matches tasks with volunteers' time windows, and optimizes task distribution using smart algorithms. Experimental results show that volunteer service systems with integrated intelligent scheduling management significantly improve task allocation accuracy and volunteer satisfaction. This research provides new ideas and practical basis for the intelligent development of volunteer services. © 2024 IEEE.

关键词： Digital family digital platform volunteer service

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An English Pronunciation Evaluation Model Based on Acoustic Phonetics Features 4

An English Pronunciation Evaluation Model Based on Acoustic ...

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4th International Conference on Computer Science and Blockchain, CCSB 2024

作者： Wang, Hongkang Guo, Qingkai Huang, Guimin Zhou, Ya Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798350356502

Oral English practice constitutes a crucial component of English language acquisition for non-native speakers;however, traditional classroom teaching methods are increasingly insufficient to address the diverse needs of learners. This paper enhances the evaluation of pronunciation quality within Computer-Assisted Language Learning (CALL) system. To assess the fluency of English learners' pronunciation, this paper introduces the innovative feature known as wordDurationRatio. Additionally, an intonation evaluation method utilizing dynamic time warping (DTW) algorithms is explored. Finally, this study incorporates support vector regression (SVR) algorithms to effectively fuse features, enhancing the assessment result of pronunciation quality. © 2024 IEEE.

关键词： Support vector regression

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