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Asian control Conference

作者： Yuzhu Duan Ziwen Yang Shanying Zhu Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Ministry of Education of China Shanghai P. R. China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The Industrial Internet of Things (IIoT) is increasingly emerging as a novel paradigm for information exchange within industrial production environments. To facilitate the efficient operation of IIoT, there is an urgent requirement for communication-efficient methods to transmit extensive production data. This paper proposes a communication-efficient distributed optimization algorithm tailored for the strongly convex and smooth convex optimization problems over a directed graph. To encompass a broader class of compressors, the assumption of compressor is relaxed to contain both relative and absolute errors. To mitigate compression errors, we adopt differential compression technique and dynamic scaling factor in the algorithm. In particular, under this compression assumption, a non-uniform quantizer is introduced to enable finite-bit transmission over communication channels and an upper bound of the required bits with this quantizer is provided. Moreover, we prove the linear convergence of the proposed algorithm with compression, and numerical examples are provided to verify the performance of the proposed algorithm.

关键词： Upper bound Heuristic algorithms Directed graphs Production Compressors Convex functions Optimization

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Model Predictive control for T-S Fuzzy Markovian Jump systems Using Dynamic Prediction Optimization

arXiv

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arXiv 2024年

作者： Zhang, Bin Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

In this paper, the model predictive control (MPC) problem is investigated for the constrained discrete-time Takagi-Sugeno fuzzy Markovian jump systems (FMJSs) under imperfect premise matching rules. To strike a balance between initial feasible region, control performance, and online computation burden, a set of mode-dependent state feedback fuzzy controllers within the frame of dynamic prediction optimizing (DPO)-MPC is delicately designed with the perturbation variables produced by the predictive dynamics. The DPO-MPC controllers are implemented via two stages: at the first stage, terminal constraints sets companied with feedback gain are obtained by solving a "min-max" problem;at the second stage, and a set of perturbations is designed felicitously to enlarge the feasible region. Here, dynamic feedback gains are designed for off-line using matrix factorization technique, while the dynamic controller state is determined for online over a moving horizon to gradually guide the system state from the initial feasible region to the terminal constraint set. Sufficient conditions are provided to rigorously ensure the recursive feasibility of the proposed DPO-MPC scheme and the mean-square stability of the underlying FMJS. Finally, the efficacy of the proposed methods is demonstrated through a robot arm system example. © 2024, CC BY.

关键词： Predictive control systems

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Research on Risk Management of Petrochemical Supply Chain Based on Network Dynamic Evolution Model

Research on Risk Management of Petrochemical Supply Chain Ba...

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Chinese Intelligent Automation Conference, CIAC 2021

作者： Pan, Chang-chun Huang, Xiaohao Sun, Weiqi Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9789811663710

This paper studies the quantitative measurement method of risk occurrence and possible spread among petrochemical supply chain enterprise nodes. Combined with the characteristics of petrochemical supply chain network, a risk propagation model of the supply chain based on cascading failure process is proposed, and a simulation experiment of risk propagation is carried out to investigate the different model parameters and different risk source enterprises on the communication process. According to experimental results, this paper puts forward targeted preventive measures to achieve the prevention and control of supply chain risk, which has important guiding significance for the regular operation of the petrochemical supply chain. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Risk management

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An Unsupervised Person Search Method for Video Surveillance 22

An Unsupervised Person Search Method for Video Surveillance

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8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Feng, Deying Yang, Jie Wei, Yanxia Xiao, Hairong Zhang, Laigang School of Mechanical and Automotive Engineering Liaocheng University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Liaocheng University China

ISBN: (纸本)9781450396110

We propose an unsupervised person search method for video surveillance. This method considers both the spatial features of persons within each frame and the temporal relationship of the same person among different frames. Thus, the spatial features are extracted by region convolutional neural network, and the temporal relationship is organized by gate recurrent unit. The spatio-temporal features are generated by the following average pooling layer and indexed by locality sensitive hashing. A surveillance video database is constructed to evaluate the proposed method, and the experimental results demonstrate that our method improves the search accuracy by utilizing the spatio-temporal features. © 2022 ACM.

关键词： Monitoring

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SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds

arXiv

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arXiv 2024年

作者： Wang, Yanbo Zhao, Wentao Cao, Chuan Deng, Tianchen Wang, Jingchuan Chen, Weidong Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

Although LiDAR semantic segmentation advances rapidly, state-of-the-art methods often incorporate specifically designed inductive bias derived from benchmarks originating from mechanical spinning LiDAR. This can limit model generalizability to other kinds of LiDAR technologies and make hyperparameter tuning more complex. To tackle these issues, we propose a generalized framework to accommodate various types of LiDAR prevalent in the market by replacing window-attention with our sparse focal point modulation. Our SFPNet is capable of extracting multi-level contexts and dynamically aggregating them using a gate mechanism. By implementing a channel-wise information query, features that incorporate both local and global contexts are encoded. We also introduce a novel large-scale hybrid-solid LiDAR semantic segmentation dataset for robotic applications. SFPNet demonstrates competitive performance on conventional benchmarks derived from mechanical spinning LiDAR, while achieving state-of-the-art results on benchmark derived from solid-state LiDAR. Additionally, it outperforms existing methods on our novel dataset sourced from hybrid-solid LiDAR. Code and dataset are available at https://***/Cavendish518/SFPNet and https://***. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Topology-Preserving Second-Order Consensus: A Strategic Compensation Approach

Topology-Preserving Second-Order Consensus: A Strategic Comp...

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IEEE Conference on Decision and control

作者： Zitong Wang Yushan Li Xiaoming Duan Jianping He Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

The interaction topology plays a significant role in the collaboration of multiagent systems. How to preserve the topology against inference attacks has become an imperative task for security concerns. In this paper, we propose a distributed topology-preserving algorithm for second-order multi-agent systems by adding noisy inputs. The major novelty is that we develop a strategic compensation approach to overcome the noise accumulation issue in the second-order dynamic process while ensuring the exact second-order consensus. Specifically, we design two distributed compensation strategies that make the topology more invulnerable against inference attacks. Furthermore, we derive the relationship between the inference error and the number of observations by taking the ordinary least squares estimator as a benchmark. Extensive simulations are conducted to verify the topology-preserving performance of the proposed algorithm.

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Differential Game with Mixed Strategies: A Weak Approximation Approach

Differential Game with Mixed Strategies: A Weak Approximatio...

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IEEE Conference on Decision and control

作者： Tao Xu Wang Xi Jianping He Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

This paper utilizes the weak approximation method to analyze differential games that involve mixed strategies. Mixed strategies have the potential to produce unique strategic behaviors, whereas traditional models and tools in pure strategy games cannot be directly applied. Based on the stochastic processes with independent increments, we define the mixed strategy without assuming the knowledge of the opponents' strategy and system state. However, this general mixed strategy poses challenges in evaluating game payoff and game value. To overcome these challenges, we utilize the weak approximation method to employ a stochastic differential game to characterize the dynamics of the mixed strategy game. We demonstrate that the game's payoff function can be precisely approximated with an error of the same scale as the step size. Furthermore, we estimate the upper and lower value functions of the weak approximated game to analyze the existence of game value. Finally, we provide numerical examples to illustrate and elaborate on our findings.

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Vision-Based Autonomous Landing of a Quadrotor UAV on a Double-Layered Nested Landing Marker

Vision-Based Autonomous Landing of a Quadrotor UAV on a Doub...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Mu, Lingxia Zhang, Yuan Xin, Jing Zhang, Youmin School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Department of Mechanical and Industrial Engineering Concordia University MontrealH3G 1M8 Canada

ISBN: (纸本)9789811966125

This paper focuses on the vision-based autonomous landing mission of a quadrotor unmanned aerial vehicle (UAV). A double-layered nested Aruco landing marker is designed which can adapt to the situation that the field of sight of airborne camera changes as the UAV’s altitude decreases during the landing. Then, considering that the landing marker might be obstructed in certain situation, traditional Aruco detection method cannot effectively recognize marker. A YOLOv4 deep learning algorithm is used for marker detection. In addition, to address the problem of false detection in some test results, normalized Wasserstein distance is used to replace the non-maximum suppression to deal with redundant frames. The UAV’s relative location to the marker is then calculated and landing mission is finally achieved by the image-based visual servoing strategy. The simulation on Gazebo demonstrates that the designed marker is effective for the UAV landing mission and the revised YOLOv4 detection algorithm can increase detection results accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Antennas

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Robust Stability of Linear Time-Invariant systems with Hybrid Uncertainties

Robust Stability of Linear Time-Invariant Systems with Hybri...

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Automation, control and Electronics Engineering (CACEE), International Conference on

作者： Yangxuan Li Junguo Lu Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai People’s Republic of China

This paper presents a study on the robust stability analysis of linear time-invariant systems with parameter uncertainties and norm-bounded uncertainties. By utilizing the structured singular value, necessary and sufficient conditions for robust stability are derived. Based on the stability condition, the stability margin of the uncertain system is obtained from the skewed structured singular value. Additionally, numerical simulation results are provided to validate the effectiveness of the proposed methods.

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Adaptive Multi-weight Infrared and Visible Image Fusion via Multi-scale Transformation

Adaptive Multi-weight Infrared and Visible Image Fusion via ...

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第42届中国控制会议

作者： Tongyuehao Zhou Monan Zhang Yichen Li Wei Zhou Wenbin Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China PLA 91550

In image fusion,the desirable fused image is to obtain advantage information from different images of the same *** for the fusion of the infrared image and the visible image that have distinct features,this paper proposes an adaptive multiweight fusion based on multi-scale *** method designs different weight matrices according to the characteristics of the infrared image and the visible *** can also adaptively adjusts the weight size according to the *** on the difference of information entropy between infrared images and visible images,the method of this paper can keep the important information as much as *** results prove the method of this paper is fast and *** also has certain superiority compared with other methods.

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