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Opportunistic Wireless control Over State-Dependent Fading Channels

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arXiv 2022年

作者： Wang, Shuling Li, Peizhe Zhu, Shanying Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

The heterogeneous system consisting of the wireless control system (WCS) and mobile agent system (MAS) is ubiquitous in Industrial Internet of Things (IIoT) systems. Within this system, the positions of mobile agents may lead to shadow fading on the wireless channel that the WCS is controlled over and can significantly compromise the WCS’s performance. This paper focuses on the controller design for the MAS to ensure the performance of WCS in the presence of WCS and MAS coupling. Firstly, the constrained finite field network (FFN) with profile-dependent switching topology is adopted to proceed the operational control for the MAS. By virtue of the algebraic state space representation (ASSR) method, an equivalent form is obtained for the WCS and MAS coupling. A necessary and sufficient condition in terms of constrained set stabilization is then established to ensure the Lyapunov-like performance with expected decay rate. Finally, a graphical method together with the breath-first searching is provided to design state feedback controllers for the MAS. With this method, it is easy to check the constrained set stabilization of MAS and to ensure the performance requirements of WCS in the presence of WCS and MAS coupling. The study of an illustrative example shows the effectiveness of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： controllers

How to Share: Balancing Layer and Chain Sharing in Industrial Microservice Deployment

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arXiv 2022年

作者： Liu, Yuxiang Yang, Bo Wu, Yu Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

With the rapid development of smart manufacturing, edge computing-oriented microservice platforms are emerging as an important part of production control. In the containerized deployment of microservices, layer sharing can reduce the huge bandwidth consumption caused by image pulling, and chain sharing can reduce communication overhead caused by communication between microservices. The two sharing methods use the characteristics of each microservice to share resources during deployment. However, due to the limited resources of edge servers, it is difficult to meet the optimization goals of the two methods at the same time. Therefore, it is of critical importance to realize the improvement of service response efficiency by balancing the two sharing methods. This paper studies the optimal microservice deployment strategy that can balance layer sharing and chain sharing of microservices. We build a problem that minimizes microservice image pull delay and communication overhead and transform the problem into a linearly constrained integer quadratic programming problem through model reconstruction. A deployment strategy is obtained through the successive convex approximation (SCA) method. Experimental results show that the proposed deployment strategy can balance the two resource sharing methods. When the two sharing methods are equally considered, the average image pull delay can be reduced to 65% of the baseline, and the average communication overhead can be reduced to 30% of the baseline. Copyright © 2022, The Authors. All rights reserved.

关键词： Production control

Dual identification optical sensor for sodium benzoate and potassium sorbate based on UV-DAS combined with SEP-CNN-TL

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Food control 2025年

作者： Junfeng Wang Rui Zhu Jie Gao Fei Xie Mu Li Changyin Li Yungang Zhang Hongbin Lin Key Laboratory of Intelligent Control and Neural Information Processing Ministry of Education Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China

Simultaneous and accurate detection of sodium benzoate (SB) and potassium sorbate (PS) is crucial for ensuring food safety and protecting human health, given their prevalent application as food preservatives and the significant hazards associated with misuse. A dual identification optical sensor for SB and PS is developed based on ultraviolet direct absorption spectroscopy (UV-DAS) coupled with spectral expansion, convolutional neural network, and transfer learning (SEP-CNN-TL) model in this paper. An SEP method is proposed to address the challenge of acquiring extensive spectral data by exploiting the correlation between concentration and absorbance. Then the CNN-TL model is constructed to minimize the impact of spectral overlap on predictive accuracy. The CNN model is pre-trained using combined absorption spectra (CAS) generated by superimposing the single-component solutions spectra of SB and PS, on which the TL model is trained using mixed absorption spectra (MAS) directly derived from the mixed solutions spectra of the two to fine-tune the CNN model. The model achieves correlation coefficients (R 2 ) of 0.9993 for SB and 0.9995 for PS, with mean absolute errors (MAE) of 0.065 μg/mL and 0.061 μg/mL, respectively. This sensor has a limit of quantification (LOQ) of 0.112 μg/mL for SB and 0.108 μg/mL for PS. Its practical effectiveness has been validated through field testing on beverages, achieving recoveries of 95.36% to 98.04% for SB and 98.33% to 99.83% for PS. This research introduces an innovative approach for the simultaneous detection of multiple preservatives in food products.

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On Enlarging the Domain of Attraction for Linear Systems Subject to Asymmetric Actuator Saturation

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On Enlarging the Domain of Attraction for Linear Systems Sub...

IEEE Conference on Decision and control

作者： Wenxin Lai Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai China 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 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A.

In this paper, we revisit the problem of enlarging the domain of attraction for linear systems with asymmetric actuator saturation. We partition the state space into several regions according to the sign of each input and rewrite the linear system subject to asymmetric actuator saturation as an equivalent switched system, each subsystem of which is associated with one partition of the state space and is a linear system subject to symmetric actuator saturation. Based on this equivalent representation of the system, we present a Lyapunov function, which is composed of a set of quadratic functions associated with matrices that are not required to be positive definite. We establish sufficient conditions for regional stability and, based on them, formulate optimization problems to enlarge the estimate of the domain of attraction. Simulation results illustrate the effectiveness of the proposed approach.

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Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation

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Large-scale Multiobjective Optimization via Problem Decompos...

Congress on Evolutionary Computation

作者： Lianghao Li Cheng He Ran Cheng Linqiang Pan Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China

Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective functions and the massive volume of decision space. Some large-scale multiobjective evolutionary algorithms (LSMOEAs) have recently been proposed, which have shown their effectiveness in solving some benchmarks and real-world applications. They merely focus on handling the massive volume of decision space and ignore the complexity of LSMOPs in terms of objective functions. The complexity issue is also important since the complexity grows along with the increment in the number of decision variables. Our previous study proposed a framework to accelerate evolutionary large-scale multiobjective optimization via problem reformulation for handling large-scale decision variables. Here, we investigate the effectiveness of LSMOF combined with decomposition-based MOEA (MOEA/D), aiming to handle the complexity of LSMOPs in both the decision and objective spaces. Specifically, MOEA/D is embedded in LSMOF via two different strategies, and the proposed algorithm is tested on various benchmark LSMOPs. Experimental results indicate the encouraging performance improvement benefited from the solution of the complexity issue in large-scale multiobjective optimization.

关键词： Sociology Evolutionary computation Benchmark testing Linear programming Complexity theory Statistics Optimization

Residual 3D Scene Flow Learning with Context-Aware Feature Extraction

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arXiv 2021年

作者： Wang, Guangming Hu, Yunzhe Wu, Xinrui Wang, Hesheng Department of Automation Key Laboratory of System Control Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

Scene flow estimation is the task to predict the point-wise or pixel-wise 3D displacement vector between two consecutive frames of point clouds or images, which has important application in fields such as service robots and autonomous driving. Although many previous works have explored greatly on scene flow estimation based on point clouds, there are two problems that have not been noticed or well solved before: 1) Points of adjacent frames in repetitive patterns may be wrongly associated due to similar spatial structure in their neighbourhoods;2) Scene flow between adjacent frames of point clouds with long-distance movement may be inaccurately estimated. To solve the first problem, a novel context-aware set convolution layer is proposed in this paper to exploit contextual structure information of Euclidean space and learn soft aggregation weights for local point features. This design is inspired by human perception of contextual structure information during scene understanding with repetitive patterns. The context-aware set convolution layer is incorporated in a context-aware point feature pyramid module of 3D point clouds for scene flow estimation. For the second problem, an explicit residual flow learning structure is proposed in the residual flow refinement layer to cope with long-distance movement. The experiments and ablation study on FlyingThings3D and KITTI scene flow datasets demonstrate the effectiveness of each proposed component. The qualitative results show that the problems of ambiguous inter-frame association and long-distance movement estimation are well handled. Quantitative results on both FlyingThings3D and KITTI scene flow datasets show that the proposed method achieves state-of-the-art performance, surpassing all other previous works to the best of our knowledge by at least 25%. Copyright © 2021, The Authors. All rights reserved.

关键词： Feature extraction

Understanding the Robustness of 3D Object Detection with Bird’s-Eye-View Representations in Autonomous Driving

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arXiv 2023年

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Dept. of Comp. Sci. and Tech. Institute for AI THBI Lab BNRist Center Tsinghua University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province China SAIC Motor AI Lab China Zhongguancun Laboratory China

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird’s-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDAR fusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. Code available at https: //***/zzj403/BEV_Robust. Copyright © 2023, The Authors. All rights reserved.

关键词： Birds

An Improved Method for Approximating the Infinite-horizon Value Function of the Discrete-time Switched LQR Problem

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IFAC-PapersOnLine 2023年第2期56卷 4138-4143页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR problem. In particular, we propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value function. This method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration, and thus, our method is capable of achieving a better approximation for a given computation time compared with the existing methods. Two numerical examples are presented in this paper to illustrate the effectiveness of our method.

关键词： Switched linear systems optimal control switched LQR problem

Unequal Error Protection Rateless Codes for Spatial Audio Transmission

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

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