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SSRN 2024年

作者： Zhao, Ziyu Lu, Xiaobo Zhou, Sifan Chiang, Patrick Y.I.N. School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Key Laboratory of ASIC and System Fudan University Shanghai China

Recent research in neural rendering has achieved impressive results in the field of novel view synthesis. However, high-quality view synthesis with sparse source views remains a challenging task, as the reduction in the number of source views significantly degrades the synthesis quality. In this paper, we present a novel view synthesis system that exploits RGB-D pairs from sparse source views. First, we introduce a two-branch feature extraction network to embed the geometric clues from depth maps into the texture information of color images and fuse it with regularized Fourier mapping features. Second, a distance-aware feature query method, which constructs multi-level feature maps, is proposed to ensure high-fidelity details across different distance views. Then, we apply an occupancy network to perform occupancy prediction on raw point cloud. By integrating occupancy probabilities and extracted features, we use a prediction network with geometric information as an additional input to obtain the color and density of sampled points, and synthesize the target view using neural volume rendering. To prevent model degradation and enhance efficiency, we design an efficient sampling strategy based on Gaussian Mixture Model. Moreover, we introduce pixel-wise local regularization and full-image global geometric regularization to optimize the model. Extensive experiments show that the proposed method can achieve the state-of-the-art results for novel view synthesis with sparse inputs, and the model performance has been significantly improved in different scenarios. © 2024, The Authors. All rights reserved.

关键词： Geometry

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Stackelberg Game Theoretical Learning for Multi-Agent Formation Tracking control

Stackelberg Game Theoretical Learning for Multi-Agent Format...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Haichuan Ye Haoyu Zhou Bei Ma Yongbao Wu Lei Xue School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

In this article, the formation tracking problem is discussed within a multi-agent framework. Drawing from the hierarchical model featuring a single leader and multiple followers, we use the Stackelberg game to model the system and prove the Stackelberg-Nash equilibrium exists. The solution of the preceding game is resolved by using the deep reinforcement learning algorithm and a generative communication strategy learning algorithm is proposed. The efficacy of the aforementioned methodology is validated through experimental simulations, substantiating its effectiveness.

关键词： Training Automation Network topology Games Deep reinforcement learning Topology Communication networks

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Nonrigid Object Contact Estimation With Regional Unwrapping Transformer

Nonrigid Object Contact Estimation With Regional Unwrapping ...

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International Conference on Computer Vision (ICCV)

作者： Wei Xie Zimeng Zhao Shiying Li Binghui Zuo Yangang Wang Southeast University China Ministry of Education Southeast University are Affiliated With the Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China

Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. However, existing learning-based methods focus more on contact with rigid ones from monocular images. When adopting them for nonrigid contact, a major problem is that the existing contact representation is restricted by the geometry of the object. Consequently, contact neighborhoods are stored in an unordered manner and contact features are difficult to align with image cues. At the core of our approach lies a novel hand-object contact representation called RUPs (Region Unwrapping Profiles), which unwrap the roughly estimated hand-object surfaces as multiple high-resolution 2D regional profiles. The region grouping strategy is consistent with the hand kinematic bone division because they are the primitive initiators for a composite contact pattern. Based on this representation, our Regional Unwrapping Transformer (RUFormer) learns the correlation priors across regions from monocular inputs and predicts corresponding contact and deformed transformations. Our experiments demonstrate that the proposed framework can robustly estimate the deformed degrees and deformed transformations, which makes it suitable for both nonrigid and rigid contact.

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Adaptive control for Stochastic Nonlinear systems with Input Saturation Based on Multi-dimensional Taylor Network

Adaptive Control for Stochastic Nonlinear Systems with Input...

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IEEE International Conference on Mechatronics and Automation

作者： Xiao-Yi Zheng Hong-Sen Yan Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China School of Automation Southeast University Nanjing China

For stochastic nonlinear systems with input saturation, few of the existing control methods use a suitable auxiliary system to solve input saturation problem, and most of them are for deterministic systems. In this study, according to the backstepping approach and the Lyapunov stability theorem, utilizing multi-dimensional Taylor network (MTN), an adaptive controller is presented to secure that all closed-loop signals keep bounded in probability, in which MTN is implemented to approach the uncertain function during the controller design. Moreover, the impact raised by input saturation is mitigated by designing an appropriate auxiliary system, in which the order of the auxiliary system is the same as that of the controlled system. Furthermore, unlike the majority of prior findings, the final output signal could be constrained in a mean quartic sense by an explicit expression of the input saturation error (the difference between the control signal and the saturation input) and the parameters used for design. Finally, the efficiency of the suggested control methodology is confirmed by providing an example.

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Design of low-power, high-precision wireless temperature transmitter based on WIFI

Design of low-power, high-precision wireless temperature tra...

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Jiangsu Annual Conference on Automation (JACA 2023)

作者： L. Wang X. Wang R. Jiang Y. Gao Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 People's Republic of China

In order to enhance the performance of temperature transmitters and facilitate their integration into intelligent and wireless systems, a novel design is proposed, incorporating a pseudo self-balancing electric bridge to achieve a high-precision and wide-range temperature measurement capability. This advanced transmitter not only maximizes the measurement range of thermal resistance but also ensures exceptional temperature accuracy. It seamlessly transfers data to a server through the utilization of the WIFI protocol. Furthermore, the transmitter is equipped with wireless communication capabilities, allowing data transmission through a 4-20mA current loop. The calibration and configuration processes can be conveniently carried out via a USB interface. Rigorous testing validates that the accuracy of the transmitter conforms to the stringent specifications outlined in GB/T 34072-2017 for 0.1-level temperature transmitters. Additionally, when operated with battery power, the transmitter exhibits commendably low average power consumption.

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Non-Smooth Speed control of Switched Reluctance Motor Based on Generalized Proportional Integral Observer

Non-Smooth Speed Control of Switched Reluctance Motor Based ...

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Chinese control Conference (CCC)

作者： Qingzhao Yin Zheng Tian Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

This paper investigates the speed regulation control of switched reluctance motor (SRM) systems. To improve the antidisturbance performance of SRM, a composite non-smooth control strategy is proposed. First, the structure of SRM is analyzed, and a simplified nonlinear model is obtained based on a segmented representation of the varying phase inductance. A virtual control function is introduced to represent the nonlinear part of the torque equation, whose inverse function is cascaded to linearized the nonlinear model. Second, a generalized proportional integral observer (GPIO) is constructed to estimate the lumped disturbance of the system, which is used for feedforward compensation design. Finally, a composite speed controller is designed based on a combination of finite time proportional feedback and feed-forward compensation based on GPIO (FTP+GPIO). The speed error closed-loop system can be regarded as a first-order finite time control system with bounded disturbances. Strict analysis shows that the proposed scheme can improve the anti-disturbance performance of the closed-loop system. The effectiveness of the proposed method is verified by simulation results. Moreover, it is compared with proportional feedback combining feed-forward compensation (P+GPIO) method and proportional integral (PI) control method.

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4D Myocardium Reconstruction with Decoupled Motion and Shape Model

4D Myocardium Reconstruction with Decoupled Motion and Shape...

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International Conference on Computer Vision (ICCV)

作者： Xiaohan Yuan Cong Liu Yangang Wang Southeast University China Southeast University are Affiliated With the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

Estimating the shape and motion state of the myocardium is essential in diagnosing cardiovascular diseases. However, cine magnetic resonance (CMR) imaging is dominated by 2D slices, whose large slice spacing challenges inter-slice shape reconstruction and motion acquisition. To address this problem, we propose a 4D reconstruction method that decouples motion and shape, which can predict the inter-/intra- shape and motion estimation from a given sparse point cloud sequence obtained from limited slices. Our framework comprises a neural motion model and an end-diastolic (ED) shape model. The implicit ED shape model can learn a continuous boundary and encourage the motion model to predict without the supervision of ground truth deformation, and the motion model enables canonical input of the shape model by deforming any point from any phase to the ED phase. Additionally, the constructed ED-space enables pre-training of the shape model, thereby guiding the motion model and addressing the issue of data scarcity. We propose the first 4D myocardial dataset as we know and verify our method on the proposed, public, and cross-modal datasets, showing superior reconstruction performance and enabling various clinical applications.

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Frequency Regulation Reserve Optimization Considering Flexible Resource Complementary Aggregation

Frequency Regulation Reserve Optimization Considering Flexib...

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Zirui Huang Wenbo Mao Yaping Li Kaifeng Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China China Electric Power Research Institute CO. Ltd Nanjing China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

This paper proposes a fast-solving strategy that uses the complementarity of flexible resources to aggregate and participate in frequency regulation. Firstly, this paper proposes a frequency regulation performance index which can consider the adjustment rate, response delay time, adjustable capacity and adjustment cost of flexible resources. Then, based on the index, this paper uses the K-means algorithm to cluster the resources with similar performance. Then, this paper proposes an aggregation strategy considering the complementary of multiple flexible resources. Finally, this paper improves the unit combination optimization model, so that flexible resources can participate in the optimization in the form of aggregation, and the ratio of resources can be determined in advance, reducing the number of optimization parameters and improve the efficiency of solution. In this paper, the simulation is carried out on the IEEE-118 node. The results show that the proposed scheme can effectively improve the rate of optimization solution and effectively avoid the curse of dimensionality in the face of a large number of flexible resources.

关键词： Costs Optimization models Face recognition Smart grids Performance analysis Delays Time factors Indexes Optimization Frequency control

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Fault detection method of photovoltaic system based on power change of array 4

Fault detection method of photovoltaic system based on power...

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4th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2021

作者： Tan, Chao Li, Chenxi Zhang, Kanjian Wei, Haikun Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450385053

The fault detection of photovoltaic power generation system is of great significance in photovoltaic plant management. The conventional fault detection method of photovoltaic power system requires additional sensors, and the fault detection scheme needs to be redesigned if the parameters of the photovoltaic plant change. Therefore, for large photovoltaic plants, it is necessary to develop a method that does not require the use of external sensors or the detailed parameters of the photovoltaic plant. This paper proposes a photovoltaic system fault detection method based on photovoltaic array current and voltage data. This method does not require additional sensor data such as irradiance and temperature. The failure of photovoltaic system can be detected through the change of power, and the abnormal situation of photovoltaic power station can still be detected under cloudy and shaded conditions. The advantages of this method are that there is no need for complex and diverse sensor equipment, the calculation is simple and the fault detection ability is accurate. The experimental data of Padang Poverty Power Station of State Grid has been verified. © 2021 ACM.

关键词： Fault detection

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Joint Beam Management and SLAM for mmWave Communication systems

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IEEE Transactions on Communications 2023年第10期71卷 6162-6179页

作者： Que, Hang Yang, Jie Wen, Chao-Kai Xia, Shuqiang Li, Xiao Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation Shenzhen518055 China State Key Laboratory of Mobile Network and Mobile Multimedia Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

The millimeter-wave (mmWave) communication technology, which employs large-scale antenna arrays, enables inherent sensing capabilities. Simultaneous localization and mapping (SLAM) can utilize channel multipath angle estimates to realize integrated sensing and communication design in 6G communication systems. However, existing works have ignored the significant overhead required by the mmWave beam management when implementing SLAM with angle estimates. This study proposes a joint beam management and SLAM design that utilizes the strong coupling between the radio map and channel multipath for simultaneous beam management, localization, and mapping. In this approach, we first propose a hierarchical sweeping and sensing service design. The path angles are estimated in the hierarchical sweeping, enabling angle-based SLAM with the aid of an inertial measurement unit (IMU) to realize sensing service. Then, feature-aided tracking is proposed that utilizes prior angle information generated from the radio map and IMU. Finally, a switching module is introduced to enable flexible switching between hierarchical sweeping and feature-aided tracking. Simulations show that the proposed joint design can achieve sub-meter level localization and mapping accuracy (with an error © 1972-2012 IEEE.

关键词： Mapping

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