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学者姓名：韩红桂
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Abstract ：
Point clouds and RGB images are both critical data for 3D object detection. While recent multi-modal methods combine them directly and show remarkable performances, they ignore the distinct forms of these two types of data. For mitigating the influence of this intrinsic difference on performance, we propose a novel but effective fusion model named LI-Attention model, which takes both RGB features and point cloud features into consideration and assigns a weight to each RGB feature by attention mechanism. Furthermore, based on the LI-Attention model, we propose a 3D object detection method called image attention transformer network (IAT-Net) specialized for indoor RGB-D scene. Compared with previous work on multi-modal detection, IAT-Net fuses elaborate RGB features from 2D detection results with point cloud features in attention mechanism, meanwhile generates and refines 3D detection results with transformer model. Extensive experiments demonstrate that our approach outperforms state-of-the-art performance on two widely used benchmarks of indoor 3D object detection, SUN RGB-D and NYU Depth V2, while ablation studies have been provided to analyze the effect of each module. And the source code for the proposed IAT-Net is publicly available at https://github.com/wisper181/IAT-Net.
Keyword ：
attention mechanism attention mechanism transformer transformer 3D object detection 3D object detection
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| GB/T 7714 | Ren, Keyan , Yan, Tong , Hu, Zhaoxin et al. Image attention transformer network for indoor 3D object detection [J]. | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2024 , 67 (7) : 2176-2190 . |
| MLA | Ren, Keyan et al. "Image attention transformer network for indoor 3D object detection" . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES 67 . 7 (2024) : 2176-2190 . |
| APA | Ren, Keyan , Yan, Tong , Hu, Zhaoxin , Han, Honggui , Zhang, Yunlu . Image attention transformer network for indoor 3D object detection . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2024 , 67 (7) , 2176-2190 . |
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Abstract ：
Multimodal multiobjective particle swarm optimization conducts diversity-driven evolution within the decision space to obtain equivalent solutions. However, due to the inconsistency between the diversity in the decision and objective spaces, it is difficult for evolutionary directions to reconcile the performance in both spaces. Targeted to this issue, a multimodal multiobjective particle swarm optimization with space information aggregation (MMPSO-SIA) is proposed in this paper. First, an information aggregation is proposed based on the local sensitive hash. Then, the diversity information of particles in decision space and objective spaces can be integrated into diversity metrics comprehensively. Second, a direction evaluation strategy is developed to capture the potential solutions in both search spaces. Then, effective directions of potential solutions are supplemented to obtain evolutionary guidance for particle swarm. Third, a variable learning intensity is integrated into MMPSO-SIA. Then, the evolutionary direction provided by information aggregation methods can be efficiently utilized. Finally, the benchmark function test results prove the superiority of MMPSO-SIA over other multimodal multiobjective optimization methods.
Keyword ：
multimodal multiobjective optimization multimodal multiobjective optimization evolutionary guidance evolutionary guidance information aggregation information aggregation particle swarm optimization. particle swarm optimization.
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| GB/T 7714 | Liu, Yucheng , Hou, Ying , Han, Honggui . Multimodal Multiobjective Particle Swarm Optimization with Space Information Aggregation [J]. | 2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024 , 2024 : 2372-2377 . |
| MLA | Liu, Yucheng et al. "Multimodal Multiobjective Particle Swarm Optimization with Space Information Aggregation" . | 2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024 (2024) : 2372-2377 . |
| APA | Liu, Yucheng , Hou, Ying , Han, Honggui . Multimodal Multiobjective Particle Swarm Optimization with Space Information Aggregation . | 2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024 , 2024 , 2372-2377 . |
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Abstract ：
Membrane fouling caused by many direct and indirect triggering factors has become an obstacle to the application of membrane bioreactors (MBRs). The nonlinear relationship between those factors is subject to complex causality or affiliation, which is difficult to clarify for the diagnosis of membrane fouling. To solve this problem, this paper proposes a compressible diagnosis model (CDM) based on transfer entropy to facilitate the fault diagnosis of the root cause for membrane fouling. The novelty of this model includes the following points: Firstly, a framework of a CDM between membrane fouling and causal variables is built based on a feature extraction algorithm and mechanism analysis. The framework can identify fault transfer scenarios following the changes in operating conditions. Secondly, the fault transfer topology of a CDM based on transfer entropy is constructed to describe the causal relationship between variables dynamically. Thirdly, an information compressible strategy is designed to simplify the fault transfer topology. This strategy can eliminate the repetitious affiliation relationship, which contributes to diagnosing the root causal variables speedily and accurately. Finally, the effectiveness of the proposed CDM is verified by the measured data from an actual MBR. The results of experiments demonstrate that the proposed CDM fulfills the diagnosis of membrane fouling.
Keyword ：
transfer entropy transfer entropy causal relationship causal relationship membrane fouling membrane fouling root causal variables root causal variables diagnosis diagnosis
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| GB/T 7714 | Wu, Xiaolong , Hou, Dongyang , Yang, Hongyan et al. Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (18) . |
| MLA | Wu, Xiaolong et al. "Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy" . | APPLIED SCIENCES-BASEL 14 . 18 (2024) . |
| APA | Wu, Xiaolong , Hou, Dongyang , Yang, Hongyan , Han, Honggui . Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy . | APPLIED SCIENCES-BASEL , 2024 , 14 (18) . |
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Abstract ：
Fault-tolerant control (FTC) has been developed as a remedial strategy, which can take action with fault information to inhibit the occurrence of abnormal condition, such as sludge bulking, further to ensure the safety and stability of wastewater treatment process (WWTP). However, since the coupling relationship among fault variables results in the complexity and obscurity of fault characteristic, especially in the early stage, it is difficult to extract the available fault information to design an efficient FTC. Therefore, to tackle this issue, a knowledge-guided fault-tolerant compensation control (KG-FTCC) with fault diagnosis is presented in this article. First, a knowledge fault diagnosis strategy is employed to analyze the variable causality to extract the root fault cause. Then, the proposed strategy can identify the fault characteristic with coupling relationship to assist in KG-FTCC. Second, a knowledge fault compensation mechanism, which can leverage the fault knowledge and data, is introduced in KG-FTCC to achieve the control law reconstruction. Then, the proposed KG-FTCC can catch the desired set-point to suppress the sludge bulking. Third, the stability of KG-FTCC is proved by using the Lyapunov theory. Then, the effective implementation of KG-FTCC can be guaranteed. Finally, the merit of KG-FTCC is verified in a real WWTP and a simulation application. The experimental results indicate that KG-FTCC can enhance its diagnosis and control performance to ensure the safe and stable operation of WWTP.
Keyword ：
Couplings Couplings Simulation Simulation Adaptive systems Adaptive systems Fault tolerance Fault tolerance Knowledge transfer Knowledge transfer Actuators Actuators knowledge fault diagnosis strategy knowledge fault diagnosis strategy Standards Standards stability stability Knowledge fault compensation mechanism Knowledge fault compensation mechanism Fault tolerant systems Fault tolerant systems Data mining Data mining Fault diagnosis Fault diagnosis knowledge-guided fault-tolerant compensation control (KG-FTCC) knowledge-guided fault-tolerant compensation control (KG-FTCC) sludge bulking sludge bulking
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| GB/T 7714 | Han, Honggui , Xu, Yumeng , Liu, Zheng et al. Knowledge-Guided Fault-Tolerant Compensation Control With Fault Diagnosis for Sludge Bulking [J]. | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2024 . |
| MLA | Han, Honggui et al. "Knowledge-Guided Fault-Tolerant Compensation Control With Fault Diagnosis for Sludge Bulking" . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2024) . |
| APA | Han, Honggui , Xu, Yumeng , Liu, Zheng , Sun, Haoyuan . Knowledge-Guided Fault-Tolerant Compensation Control With Fault Diagnosis for Sludge Bulking . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2024 . |
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Abstract ：
The aim of this article is to address the modeling and control problems of discrete-time Takagi-Sugeno (T-S) fuzzy systems that are affected by stochastic packet dropouts. To describe the stochastic behavior of packet dropout between the sensor-controller and controller-actuator, a consecutive packet dropout model is employed. By treating consecutive packet dropouts (CPDs) as an extension of the transmission interval, the considered T-S system is transformed into a stochastic system with bounded stochastic input delay. In addition, a novel equivalent model for the closed-loop system is proposed, which captures the nonuniform distribution of the input delay caused by CPDs. Using the obtained equivalent model, it is possible to evaluate the probability distribution of each stochastic input delay value using the formula for total probability. This approach allows us to fully consider the probability information of CPDs in subsequent stability analysis and controller design. Based on this model, delay-probability dependent stability conditions are derived using stochastic Lyapunov functionals, and controller design conditions are also provided. Finally, the correctness and conservatism reduction of the proposed design method are demonstrated using numerical examples of two physical systems described by T-S fuzzy models.
Keyword ：
Symmetric matrices Symmetric matrices Sensors Sensors discrete-time Takagi-Sugeno fuzzy systems (DTTSFs) discrete-time Takagi-Sugeno fuzzy systems (DTTSFs) stochastic input delay stochastic input delay Stability criteria Stability criteria Numerical stability Numerical stability controller design controller design Stochastic processes Stochastic processes Delays Delays Fuzzy systems Fuzzy systems Consecutive packet dropouts (CPDs) Consecutive packet dropouts (CPDs)
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| GB/T 7714 | Sun, Hao-Yuan , Hou, Shuang , Han, Hong-Gui et al. Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts [J]. | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2024 , 32 (4) : 2129-2139 . |
| MLA | Sun, Hao-Yuan et al. "Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts" . | IEEE TRANSACTIONS ON FUZZY SYSTEMS 32 . 4 (2024) : 2129-2139 . |
| APA | Sun, Hao-Yuan , Hou, Shuang , Han, Hong-Gui , Qiao, Jun-Fei . Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts . | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2024 , 32 (4) , 2129-2139 . |
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Abstract ：
针对城市污水处理过程时滞导致难以稳定控制的问题,提出一种自适应滑模控制方法 (Adaptive sliding mode control, ASMC).首先,分析推流时滞对城市污水处理生化反应过程的影响,建立时滞影响下的城市污水处理运行控制模型;其次,设计一种基于模糊神经网络的预估补偿模型,完成滞后变量的准确预测,实现控制模型中变量时刻的统一;最后,设计一种具有自适应开关增益系数的滑模控制器(Sliding mode control, SMC),实现溶解氧和硝态氮的稳定控制.将提出的自适应滑模控制方法应用于城市污水处理过程基准仿真平台,实验结果显示该方法能够实现城市污水处理运行过程稳定控制.
Keyword ：
滑模控制 滑模控制 时滞 时滞 模糊神经网络 模糊神经网络 城市污水处理过程 城市污水处理过程
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| GB/T 7714 | 韩红桂 , 秦晨辉 , 孙浩源 et al. 城市污水处理过程自适应滑模控制 [J]. | 自动化学报 , 2023 , 49 (05) : 1010-1018 . |
| MLA | 韩红桂 et al. "城市污水处理过程自适应滑模控制" . | 自动化学报 49 . 05 (2023) : 1010-1018 . |
| APA | 韩红桂 , 秦晨辉 , 孙浩源 , 乔俊飞 . 城市污水处理过程自适应滑模控制 . | 自动化学报 , 2023 , 49 (05) , 1010-1018 . |
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Abstract ：
厌氧氨氧化技术是当今最有发展前景的生物脱氮工艺,在厌氧条件下由厌氧氨氧化菌以亚硝酸盐作为电子受体将氨氮直接氧化为氮气,具有无需曝气、无需有机碳源、剩余污泥产量少等优点.然而厌氧氨氧化菌对生长环境的要求苛刻,影响因素众多,成为其大规模工程化应用的最大瓶颈.本文综述了五种主要影响因素(底物浓度、有机物、溶解氧、温度、pH值)对厌氧氨氧化的影响,并结合不同反应器类型、不同菌种针对不同情况分别讨论如何最大程度利用厌氧氨氧化技术,以期为主流污水处理中厌氧氨氧化的应用提供参考.
Keyword ：
厌氧氨氧化 厌氧氨氧化 溶解氧 溶解氧 底物浓度 底物浓度 有机物 有机物 影响因素 影响因素
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| GB/T 7714 | 韩雪恪 , 王峥嵘 , 彭永臻 et al. 几种重要因素对厌氧氨氧化过程的影响综述 [J]. | 中国环境科学 , 2023 , 43 (05) : 2220-2227 . |
| MLA | 韩雪恪 et al. "几种重要因素对厌氧氨氧化过程的影响综述" . | 中国环境科学 43 . 05 (2023) : 2220-2227 . |
| APA | 韩雪恪 , 王峥嵘 , 彭永臻 , 韩红桂 . 几种重要因素对厌氧氨氧化过程的影响综述 . | 中国环境科学 , 2023 , 43 (05) , 2220-2227 . |
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Abstract ：
This paper investigates the observer-based sampled-data control problem for networked systems with consecutive packet dropouts. A new consecutive packet dropout model is established to describe the phenomenon of packet dropout in both the sensor-controller (S-C) and controller-actuator (C-A) channels. First, the considered system with observer-based control scheme is studied in the discrete-time domain by using equivalent discretization transformation. In order to simplify subsequent analysis, matrix exponential computation is employed to transform the discrete-time system into a more tractable form. Then, the proposed new consecutive packet dropout model is taken into consideration to establish the stochastic mean square exponential stability condition. Furthermore, a novel two-step synthesis approach is used to design the observer-based controller. Finally, the effectiveness of the proposed observer-based sampled-data control approach is verified using a numerical example. In addition, the advantages of the proposed approach are validated through comparisons.
Keyword ：
sampled-data systems sampled-data systems observer-based control observer-based control consecutive packet dropouts consecutive packet dropouts controller design controller design
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| GB/T 7714 | Sun, Hao-Yuan , Han, Hong-Gui , Sun, Jian et al. Observer-based sampled-data control for networked systems with consecutive packet dropouts [J]. | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2023 , 33 (17) : 10662-10677 . |
| MLA | Sun, Hao-Yuan et al. "Observer-based sampled-data control for networked systems with consecutive packet dropouts" . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 33 . 17 (2023) : 10662-10677 . |
| APA | Sun, Hao-Yuan , Han, Hong-Gui , Sun, Jian , Qiao, Jun-Fei . Observer-based sampled-data control for networked systems with consecutive packet dropouts . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2023 , 33 (17) , 10662-10677 . |
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Abstract ：
本发明公开了一种基于强化学习最优控制的平流层飞艇轨迹跟踪方法，其具体步骤如下：建立平流层飞艇六自由度运动学和动力学模型，并将其表示为状态空间方程形式。给定期望轨迹计算期望位置和当前位置之间的误差，获得无约束的位置跟踪误差动力学模型。利用critic网络估计最优性能函数与最优控制量，以最小化估计误差为目标，获得基于最优控制输入量。获得对模型中的不确定项的估计补偿量，结合最优控制输入量与估计补偿量，获得鲁棒最优控制律。结合动力系统布局对合力和合力矩进行控制解算，得到螺旋桨转速，实现平流层飞艇自主跟踪期望轨迹。通过基于级联滤波的估计器有效抑制了未知的建模误差和外界干扰对系统的影响，控制器具有较高鲁棒性。
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| GB/T 7714 | 黄琰婷 , 张雅滨 , 韩红桂 . 一种基于强化学习最优控制的平流层飞艇轨迹跟踪方法 : CN202310411334.7[P]. | 2023-04-18 . |
| MLA | 黄琰婷 et al. "一种基于强化学习最优控制的平流层飞艇轨迹跟踪方法" : CN202310411334.7. | 2023-04-18 . |
| APA | 黄琰婷 , 张雅滨 , 韩红桂 . 一种基于强化学习最优控制的平流层飞艇轨迹跟踪方法 : CN202310411334.7. | 2023-04-18 . |
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Abstract ：
With the appearance of a huge number of reusable electronic products, the precise value evaluation has become an urgent problem to be solved in the recycling process. Traditional methods rely on manual intervention mostly. In order to make the model more suitable for the dynamic updating, this paper proposes the reinforcement learning based electronic products value prediction model, and it integrates market information to achieve timely and stable prediction results. The basic attributes and depreciation attributes of the product are modeled by two parallel neural networks separately to learn the different effects for prediction. Most importantly, the double deep Q network is adopted to fuse market information by reinforcement learning strategy, and the training on the old product data can be used to predict the following appeared product, which alleviates the cold start problem. Experiments on the real mobile phone recycling platform data verify that the model has achieved higher accuracy and it has a better generalization ability.
Keyword ：
deep Q network deep Q network reinforcement learning reinforcement learning market factor market factor electronic products value prediction electronic products value prediction
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| GB/T 7714 | Du YongPing , Jin XingNan , Han HongGui et al. Reusable electronic products value prediction based on reinforcement learning [J]. | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (7) : 1578-1586 . |
| MLA | Du YongPing et al. "Reusable electronic products value prediction based on reinforcement learning" . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES 65 . 7 (2022) : 1578-1586 . |
| APA | Du YongPing , Jin XingNan , Han HongGui , Wang LuLin . Reusable electronic products value prediction based on reinforcement learning . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (7) , 1578-1586 . |
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