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Robust Semi-Global Output Regulation of Uncertain Two-Time-Scale Systems With Input Saturation

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2025年第9期35卷 3484-3495页

作者： Lei, Yan Wang, Yan-Wu Morarescu, Irinel-Constantin Astolfi, Daniele Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China Southwest Univ Sch Elect & Informat Engn Chongqing Peoples R China Univ Lorraine CNRS CRAN Nancy France Univ Claude Bernard Lyon 1 Univ Lyon CNRS Villeurbanne France

This paper investigates the robust semi-global output regulation of uncertain linear systems with input saturation. In this setup, one cannot apply off-the-shelf techniques to reject structural uncertainties due to numerical issues caused by the two time scales but also due to technical issues generated by the input saturation. To solve this problem, we combine internal model principle with low gain technique and singular perturbation theory. Explicitly, the regulator design is based on the computation of the solutions of a Sylvester equation, which can be ill-conditioned in the two-time scales setting. To overcome this, we propose an easily solvable equation, and the existence and uniqueness of its solution are guaranteed under some standard assumptions. Accordingly, an internal model-based controller is designed such that the semi-global robust output regulation problem can be solved. In order to cope with the input saturation, we impose that the ultimate upper bound of the infinity norm of the exosystem state is limited and satisfies certain constraints. Finally, three examples are provided to illustrate the effectiveness of the results.

关键词： input saturation internal model robust output regulation two-time-scale

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Affective Brain-Computer Interfaces (aBCIs): A Tutorial

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PROCEEDINGS OF THE IEEE 2023年第10期111卷 1314-1332页

作者： Wu, Dongrui Lu, Bao-Liang Hu, Bin Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Minist Educ Image Proc & Intelligent Control Wuhan 430074 Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China Beijing Inst Technol Inst Engn Med Beijing 100811 Peoples R China

A brain-computer interface (BCI) enables a user to communicate directly with a computer using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the emotional state of the brain, which could facilitate human cognition, communication, decision-making, and health. The last decade has witnessed rapid progress in aBCI research and applications, but there does not exist a comprehensive and up-to-date tutorial on aBCIs. This tutorial fills the gap. It introduces first the basic concepts of BCIs and then, in detail, the individual components in a closed-loop aBCI system, including signal acquisition, signal processing, feature extraction, emotion recognition, and brain stimulation. Next, it describes three representative applications of aBCIs, i.e., cognitive workload recognition, fatigue estimation, and depression diagnosis and treatment. Several challenges and opportunities in aBCI research and applications, including brain signal acquisition, emotion labeling, diversity and size of aBCI datasets, algorithm comparison, negative transfer in emotion recognition, and privacy protection and security of aBCIs, are also explained.

关键词： Affective computing brain-computer interface (BCI) emotion recognition emotion regulation machine learning

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Flexible Formation Tracking control of Multiple Unmanned Surface Vessels for Navigating Through Narrow Channels with Unknown Curvatures

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第3期70卷 2927-2938页

作者： Tang, Chuancong Zhang, Hai-Tao Wang, Jun Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China City Univ Hong Kong Sch Data Sci Hong Kong Peoples R China

This article proposes a flexible formation tracking control protocol (FFTC) for multiple unmanned surface vessels (USVs) to pass through narrow water channels with unknown curvatures. An observer is developed to estimate the curvatures of channels. A flexible formation tracking control protocol is, thereby designed to steer USV fleets to pass through narrow channels in a flexible serial formation. Furthermore, the asymptotically stable conditions of the closed-loop multi-USV systems are theoretically derived. Finally, both numerical simulation and experimental results with a fleet of three HUSTER-0.3 USVs are reported to substantiate the effectiveness of the proposed FFTC protocol for navigating through narrow channel in a laboratory context.

关键词： Collision avoidance control systems formation tracking control (FTC) unmanned surface vessels (USV)

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A Polynomial Chaos Approach to Robust H8 Static Output-Feedback control With Bounded Truncation Error

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IEEE TRANSACTIONS ON AUTOMATIC control 2023年第1期68卷 470-477页

作者： Wan, Yiming Shen, Dongying E. E. Lucia, Sergio Findeisen, Rolf Braatz, Richard D. D. Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China MIT Cambridge MA 02139 USA TU Dortmund Univ D-44227 Dortmund Germany Tech Univ Darmstadt D-64227 Darmstadt Germany

article considers the H-infinity static output-feedback control for linear time-invariant uncertain systems with polynomial dependence on probabilistic time-invariant parametric uncertainties. By applying polynomial chaos theory, the control synthesis problem is solved using a high-dimensional expanded system, which characterizes stochastic state uncertainty propagation. A closed-loop polynomial chaos transformation is proposed to derive the closed-loop expanded system. The approach explicitly accounts for the closed-loop dynamics and preserves the L-2 induced gain, which results in smaller transformation errors compared to existing polynomial chaos transformations. The effect of using finite-degree polynomial chaos expansions is first captured by a norm-bounded linear differential inclusion, and then addressed by formulating a robust polynomial chaos based control synthesis problem. This proposed approach avoids the use of high-degree polynomial chaos expansions to alleviate the destabilizing effect of truncation errors, which significantly reduces computational complexity. A numerical example illustrates the effectiveness of the proposed approach.

关键词： control design control system synthesis control theory H infinity control linear matrix inequalities optimal control uncertain systems

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Coupling Bracket Segmentation and Tooth Surface Reconstruction on 3D Dental Models 26th

Coupling Bracket Segmentation and Tooth Surface Reconstructi...

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26th International Conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Tan, Yuwen Xiang, Xiang Chen, Yifeng Jing, Hongyi Ye, Shiyang Xue, Chaoran Xu, Hui Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Sch Artificial Intelligence & Automat Wuhan Peoples R China Sichuan Univ West China Hosp Stomatol State Key Lab Oral Dis Natl Clin Res Ctr Oral Dis Chengdu Peoples R China

ISBN: (纸本)9783031439865;9783031439872

Delineating and removing brackets on 3D dental models and then reconstructing the tooth surface can enable orthodontists to premake retainers for patients. It eliminates the waiting time and avoids the change of tooth position. However, it is time-consuming and laborintensive to process 3D dental models manually. To automate the entire process, accurate bracket segmentation and tooth surface reconstruction algorithms are of high need. In this paper, we propose a graph-based network named BSegNet for bracket segmentation on 3D dental models. The dynamic dilated neighborhood construction and residual connection in the graph network promote the bracket segmentation performance. Then, we propose a simple yet effective projection-based method to reconstruct the tooth surface. We project the vertices of the hole boundary on the tooth surface onto a 2D plane and then triangulate the projected polygon. We evaluate the performance of BSegNet on the bracket segmentation dataset and the results show the superiority of our method. The framework integrating the segmentation and reconstruction achieves a low reconstruction error and can be used as an effective tool to assist orthodontists in orthodontic treatment.

关键词： 3D dental surface bracket segmentation surface reconstruction deep learning orthodontic treatment

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Memristive Circuit Design of Quantized Convolutional Auto-Encoder

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2023年第4期7卷 1301-1313页

作者： Zhang, Yaozhong Wang, Xiaoping Yang, Chao Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Guangxi Univ Sci & Technol Sch Comp Sci & Technol Liuzhou 545006 Peoples R China

This work proposes a memristor-based quantized convolutional auto-encoder (MQCAE) and applies it in an image denoising application. The pulse width or amplitude is gradually tuned by incremental steps in current memristive programming methods, which can be extremely time-consuming. In this work, a multi-level programming method without incremental steps is proposed. MQCAE is composed of five kinds of network layers: convolution layers, deconvolution layers, activation function layers, batch normalization layers and max-pooling layers. We design a memristive circuit for realizing convolution and deconvolution with different kernel parameters. The proposed circuit generates one output feature row every cycle. Analog data buffers are designed to store the intermediate data among network layers. In addition, a reconfigurable analog circuit for realizing activation functions and batch normalization is presented. By using analog temp modules, convolution layers and max-pooling layers are able to compute simultaneously. We construct the MQCAE and introduce the pipeline technique among network layers based on the circuit modules. As a result, MQCAE is able to process one FashionMNIST image in 36 cycles with clock frequency 20 kHz. Finally, we verify the effectiveness of MQCAE in an image denoising task. The results show that the denoising performance of proposed scheme is close to software model while the processing speed is faster.

关键词： Acceleration memristor crossbar array convolutional auto-encoder image denoising quantization

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ScLSTM: single-cell type detection by siamese recurrent network and hierarchical clustering

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BMC BIOINFORMATICS 2023年第1期24卷 1-15页

作者： Jiang, Hanjing Huang, Yabing Li, Qianpeng Feng, Boyuan Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Inst Artificial Intelligence Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Wuhan Univ Dept Pathol Renmin Hosp Wuhan 430060 Peoples R China Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China

MotivationCategorizing cells into distinct types can shed light on biological tissue functions and interactions, and uncover specific mechanisms under pathological conditions. Since gene expression throughout a population of cells is averaged out by conventional sequencing techniques, it is challenging to distinguish between different cell types. The accumulation of single-cell RNA sequencing (scRNA-seq) data provides the foundation for a more precise classification of cell types. It is crucial building a high-accuracy clustering approach to categorize cell types since the imbalance of cell types and differences in the distribution of scRNA-seq data affect single-cell clustering and visualization *** achieve single-cell type detection, we propose a meta-learning-based single-cell clustering model called ScLSTM. Specifically, ScLSTM transforms the single-cell type detection problem into a hierarchical classification problem based on feature extraction by the siamese long-short term memory (LSTM) network. The similarity matrix derived from the improved sigmoid kernel is mapped to the siamese LSTM feature space to analyze the differences between cells. ScLSTM demonstrated superior classification performance on 8 scRNA-seq data sets of different platforms, species, and tissues. Further quantitative analysis and visualization of the human breast cancer data set validated the superiority and capability of ScLSTM in recognizing cell types.

关键词： Single-cell ScRNA-seq Siamese LSTM Cell type detection

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Dual-Camera All-in-Focus Neural Radiance Fields

arXiv

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arXiv 2025年

作者： Luo, Xianrui Wu, Zijin Peng, Juewen Sun, Huiqiang Cao, Zhiguo Lin, Guosheng Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Singapore639798 Singapore

We present the first framework capable of synthesizing the all-in-focus neural radiance field (NeRF) from inputs without manual refocusing. Without refocusing, the camera will automatically focus on the fixed object for all views, and current NeRF methods typically using one camera fail due to the consistent defocus blur and a lack of sharp reference. To restore the all-in-focus NeRF, we introduce the dual-camera from smartphones, where the ultra-wide camera has a wider depth-of-field (DoF) and the main camera possesses a higher resolution. The dual camera pair saves the high-fidelity details from the main camera and uses the ultra-wide camera’s deep DoF as reference for all-in-focus restoration. To this end, we first implement spatial warping and color matching to align the dual camera, followed by a defocus-aware fusion module with learnable defocus parameters to predict a defocus map and fuse the aligned camera pair. We also build a multi-view dataset that includes image pairs of the main and ultra-wide cameras in a smartphone. Extensive experiments on this dataset verify that our solution, termed DC-NeRF, can produce high-quality all-in-focus novel views and compares favorably against strong baselines quantitatively and qualitatively. We further show DoF applications of DC-NeRF with adjustable blur intensity and focal plane, including refocusing and split diopter. Copyright © 2025, The Authors. All rights reserved.

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Event-Triggered Finite-Time Stabilization of Fuzzy Neural Networks With Infinite Time Delays and Discontinuous Activations

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第1期32卷 1-11页

作者： Zhou, Yufeng Zeng, Zhigang Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China Engn Res Ctr Met Automat & Measurement Technol Wuhan 430081 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist China Key Lab Image Proc & Intelligent Control Educ Wuhan 430074 Peoples R China

This article unifies the stability criteria of asymptotic, exponential, and finite-time control within a single framework for fuzzy neural networks (FNNs) with infinite time delays. First, the boundedness and differentiability for time delays are removed. Then, Lipschitz condition for activation function is relaxed, which is allowed to have jumping discontinuous points. To stabilize FNNs, the analytical method is established by comparison principle, contradiction method and inequality techniques. Moreover, different from the traditional Lyapunov method and finite-time stability theorem, several sufficient conditions are deduced and the suppression functions are designed to guarantee asymptotic, exponential, and finite-time stabilization for FNNs by adjusting the parameters of the same controller. There is not necessary to construct the complex integral-type Lyapunov functional to deal with infinite time delays and to design power function in controller for finite-time stabilization. In addition, the designed event-triggered mechanism has the inherent advantages of saving communication resources and indirectly eliminates the chattering caused by signum function. Finally, simulations are presented to illustrate the feasibility and effectiveness of the theoretical results.

关键词： Fuzzy neural networks Fuzzy control Delay effects Artificial neural networks Synchronization Stability criteria control systems Discontinuous activation event-triggered control finite-time stabilization fuzzy neural networks (FNNs) infinite time delay

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A time-coded multi-concentration microfluidic chemical waveform generator for high-throughput probing suspension single-cell signaling

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Chinese Chemical Letters 2022年第6期33卷 3091-3096页

作者： Yiran Guo Peng Chen Zhaolong Gao Yiwei Li Shunji Li Xiaojun Feng Bi-Feng Liu The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics and Molecular Imaging Key Laboratory Systems Biology ThemeDepartment of Biomedical EngineeringCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

The cellular response to the complex extracellular microenvironment is highly dynamic in time and type of extracellular *** reconstructing this process and analyzing the changes in receptor conformation on the cell membrane surface and intracellular or intercellular signaling has been a major challenge in analytical chemistry and biophysical *** this paper,a time-coded multiconcentration microfluidic chemical waveform generator was developed for the dynamic signaling probing with single-cell array of high temporal resolution,high throughput,and multi-concentration combination *** on innovative microchannel structure,sophisticated external control methods and multiplexing technology,the system not only allowed for temporally sequential permutations of the four concentrations of stimuli(time code),but also generated pulsed and continuous waveforms at different frequencies in a highly controllable ***,the single-cell trap array was set up to efficiently capture cells in suspension,dramatically increasing throughput and reducing experiment preparation *** maximum frequency of the platform was 1 Hz,and one cell could be stimulated at multiple *** show the ability of the system to investigate rapid biochemical events in high throughput,pulse stimulation and continuous stimulation of different frequencies and different time codes,combined with four concentrations of histamine(HA),were generated for probing G protein-coupled receptor(GPCR)signaling in He La ***,statistical analysis was performed for the mean peak height and mean peak area of the cellular *** believe that the time-coded multi-concentration microfluidic chemical waveform generator will provide a novel strategy for analytical chemistry,biophysics,cell signaling,and individualized medicine applications.

关键词： Microfluidics Dynamic stimulation Time code High-throughput Single-cell array

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