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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Chao Chen Haoyu Li Chaochen Gu Department of Automation Ministry of Education of China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The H-type two-axis linear plane motion platform with dual gantry drive is one of the most crucial components in contour processing equipment. The dual gantry structure employs independently controlled dual-side motors to collectively drive the motion of the gantry crossbeam axis. While the introduction of dual gantry drive brings higher single-axis positioning accuracy and greater operational speed to contour processing *** these issues, this paper starts with the dynamic modeling of the dual gantry H-type plane motion platform. It modifies and extends the task coordinates within the framework of the Global Task Coordinate Frame (GTCF). Subsequently, it effectively addresses the coordination between axes and the synchronization of dual drive in the task space, obtaining both motion coordination and dual-axis synchronization capabilities, leading to more accurate contour error calculation and evaluation. The paper includes a comprehensive design of experiments to assess the dual gantry synchronization performance in contour control. The proposed control method is compared with the traditional GTCF-based contour control method, demonstrating the effectiveness and superiority of the integrated coordination and synchronization contour control method.

关键词： Accuracy Uncertainty Tracking Robot kinematics Dynamics Aerospace electronics Motors

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A Timeslot Clustering-Based Hybrid Traffic Scheduling in Time-Sensitive Networking

A Timeslot Clustering-Based Hybrid Traffic Scheduling in Tim...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Zhihao Yang Shouliang Wang Qimin Xu Xin Li Cailian Chen Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

The development of Industrial Internet of Things necessitates deterministic transmission of hybrid traffic with varying real-time requirements. Time-Sensitive Networking offers schemes combining scheduling mechanisms like the Time-Aware Shaper (TAS) and Cyclic Queuing and Forwarding (CQF). Current methods utilize the combination of TAS&CQF to schedule Time-Triggered (TT) and Audio-Video Bridging (AVB) traffic under corresponding mechanisms, respectively. However, the prior TT traffic orchestration restricts the scheduling solution space of AVB traffic, decreasing the effectiveness of combination and finally resulting in low schedulability. In this paper, we focus on enhancing the schedulability of TT&AVB scheduling by integrating TAS and Cyclic Specified Queuing and Forwarding (CSQF), which brings larger scheduling solution space to AVB traffic. The integration of TAS&CSQF is proposed by analyzing the impact of TAS on CSQF to expand the allocatable resource for AVB traffic. Then TAS&CSQF scheduling model is formulated to ensure deterministic requirements. Within this model, Timeslot Clustering Optimization (TCO) is proposed to optimize the scheduling solution space of AVB traffic and slice timeslot by refining the scheduling of TAS. Based on TCO, Flow Congestion Metric (FCM) is designed to improve schedulability by the congestion level of each link. An FCM-based algorithm is further presented to generate TT&AVB solutions incrementally. Simulation results demonstrate that our method reduces scheduling time cost by over 168 times and improves schedulability by 32% for 3000 flows compared to existing methods.

关键词： Measurement Schedules Job shop scheduling Simulation Refining Real-time systems Internet Informatics Optimization Industrial Internet of Things

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Model predictive control of event triggering in silicon single crystal growth processes

Model predictive control of event triggering in silicon sing...

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2022 Chinese Automation Congress, CAC 2022

作者： Li, Yankai Ren, Biao Liu, Ding Xi'An University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an710048 China

ISBN: (纸本)9781665465335

In this paper, the control issue of the semiconductor silicon monocrystalline growth process is studied through an event triggered model prediction approach. Firstly, a state-space model of silicon monocrystalline growth process is developed to describe the energy conversion and the dynamics and the geometry of the isodiametric stage silicon monocrystalline via the Czochralski method. Secondly, a small perturbation linearization is used to obtain a linear continuous model, which is translated into a linear discrete model under zero-order retainers. Finally, an event triggered model prediction controller is established to decrease the calculation of model prediction in the rolling optimization process. Based on experimental results, the event-triggered model prediction control algorithm is confirmed to be an effectively control scheme for the silicon monocrystalline growth process. © 2022 IEEE.

关键词： Model predictive control

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Leader-Follower Consensus on Matrix-Weighted Switching Networks

Leader-Follower Consensus on Matrix-Weighted Switching Netwo...

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International Conference on control and Automation (ICCA)

作者： Kai Wang Lulu Pan Haibin Shao Dewei Li Yuanlong Li Shaoying He Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper examines the consensus problem on leader-follower matrix-weighted undirected switching networks. First, we introduce the leader-follower matrix-weighted integral network for analyzing such a category of networks. The connection between the null space of matrix-valued Laplacian associated with the integral network and that associated with the series of switching matrix-weighted networks has been established. Under some mild assumptions, sufficient conditions for leader-follower consensus under matrix-weighted periodic switching networks are provided. Simulation results are presented to demonstrate the theoretical results.

关键词： Sufficient conditions Laplace equations Automation Simulation Null space Switches

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Improved Spatial Registration Algorithm for Sensors on Multiple Mobile Platforms

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 638-648页

作者： LÜRunyan PENG Na WU Yi CAI Yunze Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Shanghai Aerospace Electronic Technology Institute Shanghai Academy of Spaceflight TechnologyShanghai201109China Alibaba(China)Co. Ltd.Hangzhou311121China

This paper focuses on the spatial registration algorithm under the earth-center earth-fixed(ECEF)coordinate system for multiple mobile *** sensor measurement biases are discussed with the attitude information of the platform into ***,the biased measurement model is ***,the maximum likelihood registration(MLR)algorithm is discussed to simultaneously estimate the measurement biases and the target ***,an improved online MLR(IMLR)algorithm is proposed through a sliding window of adaptive *** results demonstrate that the proposed IMLR algorithm effectively improves the realtime ability of the system and can approach similar estimation accuracy to the conventional MLR algorithm.

关键词： spatial registration 3D sensors improved online maximum likelihood registration(IMLR)

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Prioritize Team Actions: Multi-Agent Temporal Logic Task Planning with Ordering Constraints

Prioritize Team Actions: Multi-Agent Temporal Logic Task Pla...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Bowen Ye Jianing Zhao Shaoyuan Li Xiang Yin Department of Automation Shanghai Jiao Tong University and the Key Laboratory of System Control and Information Processing the Ministry of Education of China Shanghai China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we investigate the problem of linear temporal logic (LTL) path planning for multi-agent systems, introducing the new concept of ordering constraints. Specifically, we consider a generic objective function that is defined for the path of each individual agent. The primary objective is to find a global plan for the team of agents, ensuring they collectively meet the specified LTL requirements. Simultaneously, we aim to maintain a pre-determined order in the values of the objective function for each agent, which we refer to as the ordering constraints. This new requirement stems from scenarios like security-aware planning, where relative orders outweigh absolute values in importance. We present an efficient algorithm to solve this problem, supported by proofs of correctness that demonstrate the optimality of our solution. Additionally, we provide a case study in security-aware path planning to illustrate the practicality and effectiveness of our proposed approach.

关键词： Uncertainty Computer aided software engineering Automation information security Linear programming Path planning Planning Logic Multi-agent systems

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OIDM: An Observability-based Intelligent Distributed Edge Sensing Method for Industrial Cyber-Physical systems

OIDM: An Observability-based Intelligent Distributed Edge Se...

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IEEE Conference on Decision and control

作者： Shigeng Wang Tiankai Jin Yehan Ma Cailian Chen Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Industrial cyber-physical systems (ICPS) integrate physical processes with computational and communication technologies in industrial settings. With the support of edge computing technology, it is feasible to schedule large-scale sensors for efficient distributed sensing. In the sensing process, observability is the key to obtaining complete system states, and stochastic scheduling is more suitable considering uncertain factors in wireless communication. However, existing works have limited research on observability in stochastic scheduling. Targeting this issue, we propose an observability-based intelligent distributed edge sensing method (OIDM). Deep reinforcement learning (DRL) methods are adopted to optimize sensing accuracy and power efficiency. Based on the system’s ability to achieve observability, we establish a bridge between observability and the number of successful sensor transmissions. Novel linear approximations of observability criteria are provided, and probabilistic bounds on observability are derived. Furthermore, these bounds guide the design of action space to achieve a probabilistic observability guarantee in stochastic scheduling. Finally, our proposed method is applied to the estimation of slab temperature in industrial hot rolling process, and simulation results validate its effectiveness.

关键词： Job shop scheduling Accuracy Processor scheduling Linear approximation Cyber-physical systems Aerospace electronics Probabilistic logic Sensor systems Observability Intelligent sensors

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Simulation study on control characteristics of semiconductor grade monocrystalline silicon growth process

Simulation study on control characteristics of semiconductor...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Yuyu Liu, Ding Song, Zezhong Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi`an University of Technology Xi'an710048 China

ISBN: (纸本)9781665465335

The growth of Czochralski(CZ) monocrystalline silicon is a nonlinear dynamic time-varying system with complex physical changes and multi-field and multi-phase coupling. In order to meet the needs of information development, it is urgent to develop large-scale, high-quality monocrystalline silicon. However, it is extremely difficult to establish an accurate control system model. Therefore, this paper considers the complex physical changes of multi-field coupling and non-linear processes in the growth of CZ monocrystalline silicon, a lumped parameter model for the growth of monocrystalline silicon is established based on energy balance model, fluid mechanics model, and geometry model, according to the internal mechanism of the monocrystalline silicon growth and the transfer mechanism of internal material flow. According to the model, a CZ monocrystalline silicon growth simulation control system is established under the Matlab/Simulink environment, and the real-time simulation data of each state variable of crystal growth is obtained. So that the control characteristics of each state variable in the crystal growth process can be analyzed. Finally, the validity of the established model is checked by the records evaluation of the semiconductor industry production process. Finally, the validity of the established model is verified based on the data analysis of the semiconductor industry production process. The results show that the model has high accuracy and can better describe the dynamic behavior of the actual monocrystalline silicon growth system. © 2022 IEEE.

关键词： MATLAB

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ProtDAT: A Unified Framework for Protein Sequence Design from Any Protein Text Description

arXiv

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arXiv 2024年

作者： Guo, Xiao-Yu Li, Yi-Fan Liu, Yuan Pan, Xiaoyong Shen, Hong-Bin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Protein design has become a critical method in advancing significant potential for various applications such as drug development and enzyme engineering. However, protein design methods utilizing large language models with solely pretraining and fine-tuning struggle to capture relationships in multi-modal protein data. To address this, we propose ProtDAT, a de novo fine-grained framework capable of designing proteins from any descriptive protein text input. ProtDAT builds upon the inherent characteristics of protein data to unify sequences and text as a cohesive whole rather than separate entities. It leverages an innovative multi-modal cross-attention, integrating protein sequences and textual information for a foundational level and seamless integration. Experimental results demonstrate that ProtDAT achieves the state-of-the-art performance in protein sequence generation, excelling in rationality, functionality, structural similarity, and validity. On 20,000 text-sequence pairs from Swiss-Prot, it improves pLDDT by 6%, TM-score by 0.26, and reduces RMSD by 1.2 Å, highlighting its potential to advance protein design. © 2024, CC BY-NC-SA.

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Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature

arXiv

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arXiv 2024年

作者： Yang, Ruikai He, Fan He, Mingzhen Yang, Jie Huang, Xiaolin The Institute of Image Processing and Pattern Recognition The MOE Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China The STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven LeuvenB-3001 Belgium

Random feature (RF) has been widely used for node consistency in decentralized kernel ridge regression (KRR). Currently, the consistency is guaranteed by imposing constraints on coefficients of features, necessitating that the random features on different nodes are identical. However, in many applications, data on different nodes varies significantly on the number or distribution, which calls for adaptive and data-dependent methods that generate different RFs. To tackle the essential difficulty, we propose a new decentralized KRR algorithm that pursues consensus on decision functions, which allows great flexibility and well adapts data on nodes. The convergence is rigorously given and the effectiveness is numerically verified: by capturing the characteristics of the data on each node, while maintaining the same communication costs as other methods, we achieved an average regression accuracy improvement of 25.5% across six real-world data sets. Copyright © 2024, The Authors. All rights reserved.

关键词： Consensus algorithm

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