检索结果-内蒙古大学图书馆

作者： Shi, Yu-Lun Liu, Zhi-Wei School of Artificial Intelligence and Automation Huazhong University of Science and Technology Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

This paper investigates secure consensus problems of nonlinear dynamical networks (NDNs) with node delay under denial-of-service (DoS) attacks, which can cause a break in communication links. It will lead to packet loss. To ensure the secure consensus in this scenario, we propose an effective impulsive control which only based on sampled information from neighbor nodes. Based on the Lyapunov stability theory and the impulsive comparison principle, an upper bound of the average impulse interval is derived to ensure the exponential consensus of NDNs under DoS attacks, and the convergence rate can be estimated. Finally, a numerical example is provided to check the theory results. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Time delay

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Defocus to focus: photo-realistic bokeh rendering by fusing defocus and radiance priors

arXiv

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arXiv 2023年

作者： Luo, Xianrui Peng, Juewen Xian, Ke Wu, Zijin Cao, Zhiguo 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

We consider the problem of realistic bokeh rendering from a single all-in-focus image. Bokeh rendering mimics aesthetic shallow depth-of-field (DoF) in professional photography, but these visual effects generated by existing methods suffer from simple flat background blur and blurred in-focus regions, giving rise to unrealistic rendered results. In this work, we argue that realistic bokeh rendering should i) model depth relations and distinguish in-focus regions, ii) sustain sharp in-focus regions, and iii) render physically accurate Circle of Confusion (CoC). To this end, we present a Defocus to Focus (D2F) framework to learn realistic bokeh rendering by fusing defocus priors with the all-in-focus image and by implementing radiance priors in layered fusion. Since no depth map is provided, we introduce defocus hallucination to integrate depth by learning to focus. The predicted defocus map implies the blur amount of bokeh and is used to guide weighted layered rendering. In layered rendering, we fuse images blurred by different kernels based on the defocus map. To increase the reality of the bokeh, we adopt radiance virtualization to simulate scene radiance. The scene radiance used in weighted layered rendering reassigns weights in the soft disk kernel to produce the CoC. To ensure the sharpness of in-focus regions, we propose to fuse upsampled bokeh images and original images. We predict the initial fusion mask from our defocus map and refine the mask with a deep network. We evaluate our model on a large-scale bokeh dataset. Extensive experiments show that our approach is capable of rendering visually pleasing bokeh effects in complex scenes. In particular, our solution receives the runner-up award in the AIM 2020 Rendering Realistic Bokeh Challenge. © 2023, CC BY-NC-ND.

关键词： image fusion

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Model Predictive control Method for Multi-motor System with Dead Zone 6

Model Predictive Control Method for Multi-motor System with ...

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6th International Conference on Automation, control and Robotics Engineering (CACRE)

作者： Fan, Genglin Tang, Xiuchuan Shen, Yi Deng, Linan Huazhong Univ Sci & Technol China EU Inst Clean & Renewable Energy Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

ISBN: (纸本)9781665435765

The multi-motor system shows excellent performance in achieving high-precision control in the applications with large load inertia, such as large-aperture telescopes and high-precision processing machine tools. However, the non-linearity of gear transmission remains a key challenge that will cause the fluctuation of angular velocity and position of the load in the multi-motor system. In order to compensate for the non-linearity in the multi-motor system, this paper introduces a dead-zone model into the spring-damper dynamics of the multi-motor system, based on which a model predictive control (MPC) method is proposed to control the angular velocity and angle of the load. The optimization target of the proposed controller is to limit the fluctuations of input torque as much as possible. The effectiveness of the dead-zone based dynamic model and the MPC method are verified by simulation.

关键词： multi-motor system MPC dead zone

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Predictor-based periodic event-triggered control for nonlinear uncertain systems with input delay

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AUTOMATICA 2022年 136卷 110055-110055页

作者： Sun, Jiankun Yang, Jun Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Loughborough Univ Dept Aeronaut & Automot Engn Loughborough LE11 3TU Leicestershire England

In this paper we investigate the problem of predictor-based periodic event-triggered control for a class of nonlinear uncertain systems subject to input delay. When only sampled-data output is available, a novel predictor-based continuous-discrete observer is first designed to estimate system state, and an event-triggered controller is second proposed to globally exponentially stabilize the nonlinear uncertain system. Under the proposed control method, the effects of input delay and sampling of output can be considerably compensated thanks to prediction technique. As a byproduct, the Zeno behavior is avoided in nature since the proposed event-triggering mechanism is detected in the form of discrete-time. Some sufficient stability conditions on maximum allowable sampling period and input delay are presented by using feedback domination technique and small-gain argument.(c) 2021 Elsevier Ltd. All rights reserved.

关键词： Periodic event-triggered control Input delay Feedback domination Nonlinear uncertain systems

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Multiple Unmanned Surface Vehicle Coverage control in Dynamic Environments

Multiple Unmanned Surface Vehicle Coverage Control in Dynami...

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Neuromorphic Computing (ICNC), International Conference on

作者： Hong Chen Dingxin He Huantao Mao Yong Yang Zhi-Wei Liu School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

This paper investigates the area coverage problem for multiple Unmanned Surface Vehicles (USVs) in dynamic environments. Multiple USVs are employed to execute the coverage task using the Voronoi Partition method for task allocation. Parameter adaptive laws are employed to estimate the parameters of the sensing function and the Voronoi cell centroids for updating the target positions in dynamic environments. Additionally, considering the influence of water surface disturbances, a nonholonomic underactuated model analysis is conducted for the USV under non-full constraints, resulting in a motion strategy for USVs. This enables the multiple USVs to effectively cover the task area. Finally, simulation results are presented to validate the effectiveness of the coverage scheme designed in this paper and the ability of USVs to effectively cover dynamic environments.

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Thermal Safety Analysis and Dynamic control Strategy for Mode Switching Process of Reversible Solid Oxide Cell System

Thermal Safety Analysis and Dynamic Control Strategy for Mod...

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Chinese control Conference (CCC)

作者： Wei Zhao Guoqiang Liu Zexin Li Xi Li Key Laboratory of Image Processing and Intelligent Control of Education Ministry School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan Hubei China

Reversible solid oxide cells (rSOC) can operate in both electrolysis mode and in fuel cell mode with high efficiency and reduced cost using the same device for both functions. When used in dynamic operation with intermittent electrical power sources, rSOC system switches from the fuel cell (SOFC) to electrolyzer (SOEC) and vice versa depending on load and grid peculiarities. This can lead to temperature profiles within the stack that can potentially lead to the failure of the stack and eventually the system. In the present work, a system-level dynamic model of rSOC is established and validated against experimental data. Subsequently, detailed dynamic thermal behavior of stack during the switching between the two modes is analyzed, and a temperature management controller based on Model Predict control method (MPC) is proposed. Gas flow and temperature at the stack inlet are controlled by air flow and bypass valves, avoiding problems associated with temperature overshoot during transient operation. The simulation results show that the temperature controller has the ability to follow fast thermal changes while maintaining thermal safety, which indicates the competitiveness of the controller.

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Bipartite Consensus of Nonlinear Discrete-time Multi-agent Systems via Variable Impulsive control

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INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2022年第2期20卷 461-471页

作者： Xu, Ziqiang Li, Chuandong Li, Yun Han, Yiyan Hu, Xiang Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing Key Lab Mobile Commun Technol Chongqing 400065 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Minist Educ Wuhan 430070 Peoples R China

This paper addresses the bipartite consensus of the nonlinear discrete-time multi-agent systems on network where cooperation and confrontation exist simultaneously. The communication graph has negative weights to represent antagonistic interaction among agents. Two kinds of distributed variable impulsive protocols are designed for case with leader and leaderless. Compared with existing fixed-time impulsive protocols, the action instant of variable impulsive protocol is in a time window and not fixed, which is more suitable for practical application. By employing Lyapunov function approach and comparison system theorem, the results reveal that the bipartite leaderless consensus and bipartite tracking consensus can be achieved. Meanwhile, the rate of bipartite consensus possess the characteristic of exponential, if some conditions are met. Finally, the effectiveness of the consensus analysis is verified by three simulation examples.

关键词： Bipartite consensus discrete-time multi-agent systems various impulsive control

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Relative-Posture-Fixed Model Predictive Human-Following control with Visibility Constraints in Obstacle Environments 8

Relative-Posture-Fixed Model Predictive Human-Following Cont...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Zhang, Yikun Huang, Jian Yu, Jinqi Zhu, Yaonan Hasegawa, Yasuhisa School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory for Image Processing and Intelligent Control Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute ShenZhen518060 China Nagoya University Department of Micronano Mechanical Science and Engineering Nagoya464-8603 Japan

ISBN: (纸本)9798350300178

The relative-posture-fixed human following is critical for the human-robot interaction and cooperation in daily scenes such as domestic service and healthcare. However, few of previous researches have discussed the difficulties faced by mobile robots in the real world, including the limitation of sensing range and hindrance from obstacles. For practicality, in this paper we investigate the relative-posture-fixed following control with collision avoidance and visibility constraints. The control task is formulated as a receding-horizon optimization problem and solved under the Nonlinear Model Predictive control (NMPC) framework, while an Extended Kalman Filter (EKF) based human trajectory predict algorithm is integrated into the robot controller. The effectiveness of the proposed algorithm is verified in a simulation, and the results demonstrate a promising performance of our controller for the human-following task in complicated environments. © 2023 IEEE.

关键词： Human robot interaction

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When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo

arXiv

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arXiv 2023年

作者： Liu, Tianqi Ye, Xinyi Zhao, Weiyue Pan, Zhiyu Shi, Min Cao, Zhiguo 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

Learning-based multi-view stereo (MVS) method heavily relies on feature matching, which requires distinctive and descriptive representations. An effective solution is to apply non-local feature aggregation, e.g., Transformer. Albeit useful, these techniques introduce heavy computation overheads for MVS. Each pixel densely attends to the whole image. In contrast, we propose to constrain non-local feature augmentation within a pair of lines: each point only attends the corresponding pair of epipolar lines. Our idea takes inspiration from the classic epipolar geometry, which shows that one point with different depth hypotheses will be projected to the epipolar line on the other view. This constraint reduces the 2D search space into the epipolar line in stereo matching. Similarly, this suggests that the matching of MVS is to distinguish a series of points lying on the same line. Inspired by this point-to-line search, we devise a line-to-point non-local augmentation strategy. We first devise an optimized searching algorithm to split the 2D feature maps into epipolar line pairs. Then, an Epipolar Transformer (ET) performs non-local feature augmentation among epipolar line pairs. We incorporate the ET into a learning-based MVS baseline, named ET-MVSNet. ET-MVSNet achieves state-of-the-art reconstruction performance on both the DTU and Tanks-and-Temples benchmark with high efficiency. Code is available at https://***/TQTQliu/ET-MVSNet. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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A Deep Learning-Based intelligent Receiver for Improving the Reliability of the MIMO Wireless Communication System

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IEEE TRANSACTIONS ON RELIABILITY 2022年第2期71卷 1104-1115页

作者： Wang, Bin Xu, Ke Zheng, Shilian Zhou, Huaji Liu, Yang Xian Univ Sci & Technol Sch Commun Engn Xian 710054 Peoples R China Sci & Technol Commun Informat Secur Control Lab Jiaxing 314000 Peoples R China Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Sch Artificial Intelligence Xian 710071 Peoples R China

Multiple-input-multiple-output (MIMO) technology is one of the most widely used communication technologies. However, with the increasing number of antennas, the complexity of the MIMO wireless communication receiver becomes higher and higher. On the other hand, the complex communication channels also raise up a great challenge to the reliability of the communication receiver system. With the rapid development and wide application of deep learning, it has been applied in the field of communication to solve some problems that are difficult to solve by the traditional methods, and thereby, improves the reliability of communication systems. Inspired by this idea, this article reviewed the signal processing process of the MIMO receiver system from the perspective of system reliability. Based on deep learning, the signal processing modules of the receiver system are jointly optimized, which changes the information recovery process of the traditional receiver and proposes the intelligent receiver for MIMO communication. In order to verify the system reliability of the intelligent receiver, this article analyzes it from the aspects of antenna numbers and channel conditions. The influence of different implementation methods of the intelligent receiver on the system reliability is also analyzed. Simulation results show that the proposed intelligent receiver for the MIMO wireless communication can recover information with a lower bit error rate and higher reliability compared with the traditional receiver under different conditions and antenna configurations.

关键词： Convolutional neural network (CNN) deep learning multiple-input-multiple-output (MIMO) receiver system reliability wireless communication system

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