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arXiv 2022年

作者： Qiu, Chenyang Zhu, Shanying Ou, Zichong Lu, Jie The School of Information Science and Technology ShanghaiTech University Shanghai201210 China The Department of Automation The Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China

In this paper, we propose a distributed stochastic second-order proximal method that enables agents in a network to cooperatively minimize the sum of their local loss functions without any centralized coordination. The proposed algorithm, referred to as St-SoPro, incorporates a decentralized second-order approximation into an augmented Lagrangian function, and then randomly samples the local gradients and Hessian matrices of the agents, so that it is computationally and memory-wise efficient, particularly for large-scale optimization problems. We show that for globally restricted strongly convex problems, the expected optimality error of St-SoPro asymptotically drops below an explicit error bound at a linear rate, and the error bound can be arbitrarily small with proper parameter settings. Simulations over real machine learning datasets demonstrate that St-SoPro outperforms several state-of-the-art distributed stochastic first-order methods in terms of convergence speed as well as computation and communication costs. Copyright © 2022, The Authors. All rights reserved.

关键词： Constrained optimization

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Distributed Online Generalized Nash Equilibrium Tracking for Prosumer Energy Trading Games

arXiv

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arXiv 2022年

作者： Xie, Yongkai Wang, Zhaojian Pang, John Z.F. Yang, Bo Guan, Xinping The Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai200240 China A*STAR 138632 Singapore

With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. Finally, numerical results with six microgrids validate the performance of the algorithm. © 2022, CC BY.

关键词： Game theory

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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International Conference on Communication Technology (ICCT)

作者： Junpeng Yin Yusun Fu Haobo Huang Jinhui Tang Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering the Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme.

关键词： Codes Error analysis Metaverse Distribution strategy Spatial audio Bit rate Symbols Communications technology Protection Spatial resolution

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SFDFNet: Single-path Feature Deep Fusion Network for Fast Semantic Segmentation of SAR Images in Building Areas

SFDFNet: Single-path Feature Deep Fusion Network for Fast Se...

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IET International Radar Conference 2023, IRC 2023

作者： Zhang, Wenyi Dai, Xiangyu Chu, Qingwei Zhang, Jiande Ding, Hao Li, Guangzuo Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences No. 9 Dengzhuang South Road Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences No. 19 Yuquan Road Beijing China QiLu Aerospace Information Research Institute No. 44 Industry North Road Jinan China

ISBN: (纸本)9781839539954

With the SAR satellites have gradually become one of the most important methods of Earth observation, rapid interpretation of SAR images has become particularly important. However, the unique imaging mechanism of SAR makes its interpretation very difficult. In this paper, we propose the SFDFNet, a deep learning-based fast segmentation method for SAR image buildings, to address the problem of difficult SAR image interpretation. A bottleneck layer of buffered large receptive field is designed in the downsampling process. The unique design of the number of channels reduces the amount of computation without affecting the extraction of information. Meanwhile, improving on the ECA module, a two-layer ECA module was proposed to increase the receptive field and improve the linear expression. Experiments show that the proposed network has excellent results in segmentation accuracy and inference speed. © The Institution of Engineering & Technology 2023.

关键词： Semantic Segmentation

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A co-design method of online learning SMC law via an input-mappping strategy

arXiv

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arXiv 2022年

作者： Yu, Yaru Li, Dewei Zhao, Dongya Xi, Yugeng Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Qingdao266580 China

The research on sliding mode control strategy is generally based on the robust approach. The larger parameter space consideration will inevitably sacrifice part of the performance. Recently, the data-driven sliding mode control method attracts much attention and shows excellent benefits in the fact that data is introduced to compensate the controller. Nevertheless, most of the research on data-driven sliding mode control relied on identification techniques, which limits its online applications due to the special requirements of the data. In this paper, an input-mapping technique is inserted into the design framework of sliding mode control to compensate for the influence generated by the unknown dynamic of the system. The major novelty of the proposed input-mapping sliding mode control strategy lies in that the sliding mode surface and the sliding mode controller are co-designed through online learning from historical input-output data to minimize an objective function. Then, the convergence rate of the system is improved significantly based on the method designed in this work. Finally, some simulations are provided to show the effectiveness and superiority of the proposed methods. © 2022, CC BY.

关键词： Sliding mode control

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Leader-following consensus for linear multi-agent systems with measurement noises

Leader-following consensus for linear multi-agent systems wi...

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第41届中国控制会议

作者： Kairui Chen Chuance Yan Zhangmou Zhu Ping Li Qijun Ren Junwei Wang School of Mechanical and Electrical Engineering Guangzhou University Key Laboratory of System Control and Information Processing Ministry of Education School of Mathematics and Statistics Guangdong University of Foreign Studies

This paper investigates a leader-following consensus problem for high-order linear multi-agent systems under a directed graph topology,containing a spanning *** is supposed that each agent can obtain full state of itself and receive its neighbors' state with noises,where the intensities of noises are vector functions of relative states of *** achieve leader-following consensus in this scene,a consensus protocol is designed,where the gain matrix is obtained by the algebraic Riccati equation and the coupling strength should be restricted in a given ***,the lower bound of the interval ensures the consensus and the upper bound of the interval is devoted to limit the efects of noises,then the designed protocol could attenuate the noises while driving the multi-agent systems to ***,a simulation example is given to show the correctness of the proposed results.

关键词： Leader-following Consensus Multi-agent systems Directed Graph Measurement Noises

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Efficient STL control Synthesis under Asynchronous Temporal Robustness Constraints

arXiv

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arXiv 2023年

作者： Yu, Xinyi Yin, Xiang Lindemann, Lars Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States

In time-critical systems, such as air traffic control systems, it is crucial to design control policies that are robust to timing uncertainty. Recently, the notion of Asynchronous Temporal Robustness (ATR) was proposed to capture the robustness of a system trajectory against individual time shifts in its sub-trajectories. In a multi-robot system, this may correspond to individual robots being delayed or early. control synthesis under ATR constraints is challenging and has not yet been addressed. In this paper, we propose an efficient control synthesis method under ATR constraints which are defined with respect to simple safety or complex signal temporal logic specifications. Given an ATR bound, we compute a sequence of control inputs so that the specification is satisfied by the system as long as each sub-trajectory is shifted not more than the ATR bound. We avoid combinatorially exploring all shifted sub-trajectories by first identifying redundancy between them. We capture this insight by the notion of instant-shift pair sets, and then propose an optimization program that enforces the specification only over the instant-shift pair sets. We show soundness and completeness of our method and analyze its computational complexity. Finally, we present various illustrative case studies. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yang, Junying Qiu, Xiaolan Shang, Mingyang Zhong, Lihua Lv, Yini Ding, Chibiao Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China Aerospace Information Research Institute Chinese Academy of Sciences National Key Laboratory of Microwave Imaging Technology Beijing China

ISBN: (纸本)9781665498142

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method. © 2021 IEEE.

关键词： azimuth multichannel SAR HRWS moving target radial velocity ambiguity

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Adaptive neural consensus tracking control for nonlinear multiagent systems with dead zone and sensor faults

Adaptive neural consensus tracking control for nonlinear mul...

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第42届中国控制会议

作者： Chengjie Huang Ci Chen Zhi Liu Zhenni Li Guangdong University of Technology Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong Key Laboratory of IoT Information Technology 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education

In this paper, an adaptive neural tracking control design is investigated for uncertain multiagent systems(MASs)with actuator dead zone and sensor faults. The adaptive control technique based on neural networks is employed to handle the uncertainty in the systems, which, however, results in a bounded tracking error from most existing works. To achieve the asymptotic tracking performance, we proposed a direct adaptive strategy via the tuning function method. Technically, a Lyapunov function with a series of smooth functions is designed, which benefits proposing of an asymptotic controller. Then, under the framework of direct adaptive control, an inverse compensation scheme, as well as a fault-tolerant mechanism, are considered for disposing of the actuator dead zone and sensor failures. As a result, user-preset tracking performance is achieved and the system error in the MASs converges to a predefined range. An example in the simulation section illustrates the effectiveness of the proposed method.

关键词：

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A Multiple Instance Learning Algorithm Using Graph Convolutional Network for Speech Content Classification 5

A Multiple Instance Learning Algorithm Using Graph Convoluti...

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5th IEEE information Technology, Networking, Electronic and Automation control Conference, ITNEC 2021

作者： Zhang, Jianyi Yao, Jiaqi Chu, Yanjie Yan, Jikun PLA Strategic Support Force Information Engineering University College of Information System Engineering Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781665415989

Recently, speech content classification begins to be formulated as a multiple instance learning (MIL) problem by some researchers. Under the MIL framework, a speech signal is considered as a bag with labels, and speech fragments are regarded as instances without corresponding labels. On this basis, we propose a new algorithm, named MI-CNN-G, for speech content classification using Graph Convolutional Network (GCN) under the MIL framework. First, we only train the MIL classifier, whose architecture is based on Convolutional Neural Network, for bag classification. Second, we utilize GCN to handle graphs composed of instance features that are the outputs of the MIL classifier for correcting the predicted probabilities of the classifier and then updated the classifier and GCN together. Finally, we employ the MI-CNN-G model to predict the labels of unknown bags. The experimental results show that GCN is effective in improving the performance of the MIL classifier on speech content classification and the MI-CNN-G model outperforms the baseline approaches in the Average Precision metric. © 2021 IEEE.

关键词： Convolutional neural networks

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