检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Zhou, Zheng Chen, Mao-Qing Liu, Si-Yuan He, Yi-Yang Peng, Yun Xia, Feng Zhao, Yong State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China National Engineering Research Center of Offshore Oil and Gas Exploration Beijing100010 China College of Information Science and Engineering Shenyang University of Technology Shenyang110870 China

The research heat of optical fiber grating quasi distributed sensing technology has been continuously increasing in recent years. Femtosecond laser micro/nano processing technology has important application potential in the fields of single-mode optical fiber multiplexing grating preparation and multi-core optical fiber multi grating writing due to its ultra-high processing accuracy and good reproducibility. In the meantime, to improve the operability of multi core fiber grating femtosecond laser writing, a device that can achieve precise 360° rotation and positioning of multi-core optical fibers has been designed and experimentally demonstrated. The bottom stabilization device enables height adjustment of the fiber rotator and groove matching with the fiber rotator for a more stable effect. The optical fiber rotator allows 360° rotation with 0.1° precision, improving precision and efficiency in multi-core optical fiber grating writing. Experimental results demonstrate that the minimum spacing between distinguishable high-quality Fiber Bragg Grating (FBG) in single-mode optical fibers to 2nm;To accommodate more FBG within a certain range and guarantee the resolution of each FBG, the minimum pitch has been further optimized to 1nm. Furthermore, to realize parallel writing technology for multi-core optical fibers with the FBG signal-to-noise ratio reaching up to 10dB. This method provides a novel approach towards realizing multiplexing for FBG fields. © 2024, The Authors. All rights reserved.

关键词： Fiber Bragg gratings

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Discrete-time Formation Control With Attitude Alignment: A Geometric Approach under Ergodic Products

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IEEE Transactions on Control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

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A Unified Alternating Optimization Framework for Joint Sensor and Actuator Configuration in LQG Systems

arXiv

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arXiv 2025年

作者： Yang, Nachuan Li, Yuzhe Shi, Ling Chen, Tongwen Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110004 China Department of Electronic and Computer Engineering Department of Chemical and Biological Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong

This paper fills a gap in the literature by considering a joint sensor and actuator configuration problem under the linear quadratic Gaussian (LQG) performance without assuming a predefined set of candidate components. Different from the existing research, which primarily focuses on selecting or placing sensors and actuators from a fixed group, we consider a more flexible formulation where these components must be designed from scratch, subject to general-form configuration costs and constraints. To address this challenge, we first analytically characterize the gradients of the LQG performance with respect to the sensor and actuator matrices using algebraic Riccati equations. Subsequently, we derive first-order optimality conditions based on the Karush–Kuhn–Tucker (KKT) analysis and develop a unified alternating direction method of multipliers (ADMM)based alternating optimization framework to address the general-form sensor and actuator configuration problem. Furthermore, we investigate three representative scenarios: sparsity promoting configuration, low-rank promoting configuration, and structure-constrained configuration. For each scenario, we provide in-depth analysis and develop tailored computational schemes. The proposed framework ensures numerical efficiency and adaptability to various design constraints and configuration costs, making it well-suited for integration into numerical solvers. Copyright © 2025, The Authors. All rights reserved.

关键词： Matrix algebra

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An Approach to Compensate for Heterogeneous Feedback and Actuation Delays in Platooning Systems

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IFAC-PapersOnLine 2022年第36期55卷 294-299页

作者： Yu Zhang Jia Hu Meng Wang Meituan Autonomous Delivery Center Beijing China Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China Chair of Traffic Process Automation Technische Universität Dresden Dresden Germany

Feedback information and actuation delays in Connected and Automated Vehicle (CAV) systems are detrimental to the string stability of CAV platoons. A generic approach is proposed to design platooning controllers that explicitly compensate for delays in communication, sensors and vehicle actuators and can be applied to platoons with different communication topology and different spacing policies. The main mechanism behind the delay-compensating design is to facilitate the host vehicle's future status (thus compensating for actuation delay) to track the preceding vehicles’ history status (thus compensating for communication and sensing delays). This is realized by reformulating the desired spacing policies. Controller analysis shows the string stability of the proposed framework is guaranteed under delays from heterogeneous sources. Simulation is carried out to compare the string-stability performance of the designed systems with the baseline controllers without delay compensation. Simulation results verify that our approach generates controllers that require smaller time gap/spacing to keep the string stability of the systems than baseline controllers.

关键词： Connected automated vehicles string stability delay compensation predictor-based control

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Inducing Desired Equilibrium in Taxi Repositioning Problem with Adaptive Incentive Design

Inducing Desired Equilibrium in Taxi Repositioning Problem w...

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IEEE Conference on Decision and Control

作者： Jianhui Li Youcheng Niu Shuang Li Yuzhe Li Jinming Xu Junfeng Wu College of Control Science and Engineering Zhejiang University Hangzhou China School of Data Science The Chinese University of Hong Kong (Shenzhen) Shenzhen China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

We study the problem of designing incentives to induce desired equilibrium in taxi repositioning problems. In this scenario, self-interested idle drivers will update their repositioning strategies with observed payoff. Meanwhile, the platform will adaptively design incentives to induce a better Nash equilibrium for global efficiency. We formulate the problem as a bi-level optimization problem where the incentive designer and idle drivers simultaneously update their decision variables. We prove that drivers' strategies will reach Nash equilibrium, and the incentive designer's objective function will reach optimality under Polyak Lojasiewicz (PL) condition. Furthermore, we derive a sufficient condition for the PL condition to hold for the upper-level objective function and lower-level agents' payoff function. Finally, we demonstrate the efficiency of the proposed method by numerical results.

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Adapting a reinforcement learning method for the distributed blocking hybrid flow shop scheduling problem 5

Adapting a reinforcement learning method for the distributed...

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5th Asian Conference on Artificial Intelligence Technology, ACAIT 2021

作者： Qin, Haoxiang Wang, Yuting Han, Yuyan Chen, Qingda Li, Junqing Liaocheng University School of Computer Science Liaocheng China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang China Shandong Normal University School of Information Science and Engineering Jinan China

ISBN: (纸本)9781665426305

With the continuous emission of energy in the past years, the environmental problems are becoming more and more serious. For example, in manufacturing, the energy efficient scheduling problem has become particularly prominent, and attracted much attention of the researchers. As a common scheduling problem in the real world, the research on distributed blocking hybrid flow shop (DBHFSP) is very few. In this paper, we will carry out a study of the problem. Because of its NP-hard character, therefore, we use the intelligent optimization algorithm to solve the problem. we firstly introduce the MILP model of the DBHFSP, then, the Q-learning method combined with the IG algorithm framework (IGQ) is proposed to solve this problem. In the experimental part, through the experiment results and comparison with other algorithms in the recent literatures, the proposed algorithm shows the excellent performance in the simulation experiment with the objective of minimizing the energy consumption. © 2021 IEEE.

关键词： Energy utilization

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Composite Nonlinear Trajectory Tracking Control of Co-Driving Vehicles Using Self-Triggered Adaptive Dynamic Programming

arXiv

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arXiv 2025年

作者： Hu, Chuan Ge, Sicheng Shi, Yingkui Gao, Weinan Guo, Wenfeng Zhang, Xi Intelligent Vehicle Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Vehicle and Mobility Tsinghua University Beijing100190 China

This article presents a composite nonlinear feedback (CNF) control method using self-triggered (ST) adaptive dynamic programming (ADP) algorithm in a human-machine shared steering framework. For the overall system dynamics, a two-degrees-of-freedom (2-DOF) vehicle model is established and a two-point preview driver model is adopted. A dynamic authority allocation strategy based on cooperation level is proposed to combine the steering input of the human driver and the automatic controller. To make further improvements in the controller design, three main contributions are put forward. Firstly, the CNF controller is designed for trajectory tracking control with refined transient performance. Besides, the self-triggered rule is applied such that the system will update in discrete times to save computing resources and increase efficiency. Moreover, by introducing the data-based ADP algorithm, the optimal control problem can be solved through iteration using system input and output information, reducing the need for accurate knowledge of system dynamics. The effectiveness of the proposed control method is validated through Carsim-Simulink co-simulations in diverse driving scenarios. © 2025, CC BY.

关键词： Steering

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Distributed online constrained convex optimization with event-triggered communication

arXiv

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arXiv 2023年

作者： Zhang, Kunpeng Yi, Xinlei Li, Yuzhe Cao, Ming Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Engineering and Technology Institute Groningen University of Groningen GroningenAG 9747 Netherlands

This paper focuses on the distributed online convex optimization problem with time-varying inequality constraints over a network of agents, where each agent collaborates with its neighboring agents to minimize the cumulative network-wide loss over time. To reduce communication overhead between the agents, we propose a distributed event-triggered online primal-dual algorithm over a time-varying directed graph. With several classes of appropriately chose decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. Finally, a numerical simulation example is provided to verify the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Directed graphs

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Input-to-output stability of the nonlinear singular systems and small-gain theorem

Input-to-output stability of the nonlinear singular systems ...

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第34届中国控制与决策会议

作者： Jiawen Li Yi Zhang Zhenghong Jin School of Science Shenyang University of Technology State Key Laboratory of Synthetical Automation for Process Industries Northeastern University School of Electrical and Electronic Engineering Nanyang Technological University

This paper studies the input-to-output stability(IOS) of nonlinear singular systems and presents the outputLagrange IOS(OL-IOS) small-gain theorem of the interconnected singular *** major contribution of this paper includes three ***,the IOS property and OL-IOS property of nonlinear singular systems is ***,the conditions of IOS small-gain theorem for the interconnected singular system is ***,the theorems for OL-IOS and the trajectory-based small-gain theorem of interconnected singular system are ***,the effectiveness of proposed method is illustrated by using a numerical example.

关键词： input-to-output stability output-Lagrange input-to-output stability nonlinear singular systems small-gain theorem

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Event-triggered impulsive synchronization of heterogeneous neural networks

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Science China(Information Sciences) 2024年第2期67卷 331-332页

作者： Zhengxin WANG Chongfang JIN Wangli HE Min XIAO Guo-Ping JIANG Jinde CAO College of Science Nanjing University of Posts and Telecommunications Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing University of Posts and Telecommunications Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology School of Automation Nanjing University of Posts and Telecommunications School of Mathematics Southeast University Yonsei Frontier Lab Yonsei University

Synchronization is one of the most important dynamics in neural networks. Several scholars have studied the quasi-synchronization of heterogeneous neural networks [1],wherein external controllers play a significant role. Impulsive control, a kind of energy-saving control, is activated instantaneously only at specific discrete moments.

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