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SSRN 2022年

作者： Cai, Lu Wang, Bo-Yuan Xiang, Fu-Cheng Zhao, Yong College of Information Science and Engineering Northeastern University Shenyang China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, a sparse fiber Bragg grating (FBG) array sensor is proposed for pressure measurement and localization on a two-dimensional plane. With a four-corner positioning model and the zooming idea, the pressure applied on a two-dimensional plane can be well measured and located based on the central wavelength variations of only six FBGs. The experimental results indicate that the maximum positioning error is about 0.11 mm and the pressure measurement error is less than 0.09N. Besides, a positioning mathematical model for the blind areas is built, and the feasibility is verified experimentally. © 2022, The Authors. All rights reserved.

关键词： Pressure sensors

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Domain transfer spatiotemporal graph network for predicting key indicators in multimode chemical processes

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Chemical engineering Science 2025年 314卷

作者： Zhu, Jialiang Yang, Chao Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In modern chemical industries, soft sensors related to key indicators are crucial in production processes, particularly for multimode chemical processes. However, challenges arise from scarce labeled data and constant process shifts, which complicate the development of these sensors. Additionally, complex process variable interactions hinder prediction interpretability. This work develops a domain transfer spatiotemporal graph network (DTSGN) regression model, tailored for cross-domain modeling in multimode chemical processes. The DTSGN model first employs graph convolution to capture spatial dependencies and gating mechanism to track temporal relationships. A Bernoulli-distributed perturbation graph enhances model robustness. By embedding constraints into conditional distribution discrepancy, the parameters for DTSGN are calibrated under the fine-tuning paradigm for new mode. Therefore, the model extends its applicability to address process shifts in multimode chemical processes. A graph explainer finally ensures interpretability by aligning learned variable graph with process knowledge, and two multimode cases evidence the proposed model's efficacy and superiority. © 2025 Elsevier Ltd

关键词： Chemical industry

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Data-Driven Distributionally Robust Mixed-Integer Control through Lifted Control Policy

arXiv

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arXiv 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China the Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China the Department of Mechanical Engineering University of Victoria VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. © 2025, CC BY.

关键词： Mixed-integer linear programming

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Finite-time Consensus for Third-Order Multi-Agent Systems with Directed Communication Networks

Finite-time Consensus for Third-Order Multi-Agent Systems wi...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Xirui Zhang Zhi-Liang Zhao Tengfei Liu Zhong-Ping Jiang School of Mathematics and Statistics Shaanxi Normal University Xi’an P. R. China School of Electrical and Control Engineering North University of China Taiyuan P. R. China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang P. R. China Department of Electrical and Computer Engineering New York University Brooklyn NY USA

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper focuses on third-order multi-agent systems with directed communication networks. It is for the first time that the finite-time consensus problem is solved for third-order multi-agent systems under digraphs containing spanning trees. Two explicit-coefficient finite-time protocols, namely, edge-based and node-based, are proposed. First, we prove that asymptotic consensus is achievable with the reduced linear protocol. Then, we show that finite-time consensus is achievable with our explicit-coefficient finite-time protocols through homogeneous theory. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed protocols.

关键词： Protocols Network topology Numerical simulation Topology Communication networks Closed loop systems Multi-agent systems

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Secure Synchronization Control for a Class of Cyber-Physical Systems With Unknown Dynamics

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1215-1224页

作者： Ning Wang Xiaojian Li College of Information Science and Engineering Northeastern UniversityShenyang 110819China State Key Laboratory of Synthetical Automation for Process Industries Northeastern Universityand with the Key Laboratory of Vibration and Control of Aero-Propulsion SystemMinistry of EducationNortheastern Universityand also with the College of Information Science and EngineeringNortheastern UniversityShenyang 110819China IEEE

This paper investigates the secure synchronization control problem for a class of cyber-physical systems(CPSs)with unknown system matrices and intermittent denial-of-service(DoS)*** the attack free case,an optimal control law consisting of a feedback control and a compensated feedforward control is proposed to achieve the synchronization,and the feedback control gain matrix is learned by iteratively solving an algebraic Riccati equation(ARE).For considering the attack cases,it is difficult to perform the stability analysis of the synchronization errors by using the existing Lyapunov function method due to the presence of unknown system *** order to overcome this difficulty,a matrix polynomial replacement method is given and it is shown that,the proposed optimal control law can still guarantee the asymptotical convergence of synchronization errors if two inequality conditions related with the DoS attacks ***,two examples are given to illustrate the effectiveness of the proposed approaches.

关键词： Algebraic Riccati equation(ARE) complex dynamical networks(CDNs) denial-of-service(DoS) secure control

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Comparative Study on Prediction Methods of Copper Concentrate Grade for a Copper Flotation process

Comparative Study on Prediction Methods of Copper Concentrat...

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第32届中国过程控制会议(CPCC2021)

作者： Zhiqiang Wang Qiang Li Dakuo He Xiang Ma School of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University SINTEF Industry

Copper flotation process is a complex industrial *** copper grade(CCG) is one of the important production indexes of flotation process,and it is also one of the important factors to determine the economic ***,the accurate prediction of CCG can not only provide operational advice for copper flotation process,but has important economic value and practical *** to the long process of copper flotation,the existence of time delay and the serious coupling of variables,the accurate prediction of CCG is *** on the analysis and study of copper flotation process,this paper adopts partial least squares(PLS),kernel partial least squares(KPLS),least squares support vector machine(LSSVM) and long short term memory(LSTM) methods to predict the CCG for a copper flotation *** of the proposed prediction models are validated by the field data in this paper and it can be learnt from the prediction evaluation indexes for root mean square error(RMSE),mean absolute error(MAE) and mean absolute percentage error(MAPE) that the prediction accuracy based on LSTM model is higher and suitable for the prediction of CCG for the copper flotation process.

关键词： copper flotation process prediction models linear and nonlinear methods copper concentrate grade

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Research on Joint Optimization of Single Train's Delay Reduction and Energy-Saving Operation Trajectory

Research on Joint Optimization of Single Train's Delay Reduc...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Yunjia Zhang Dongliang Cui Jianming Li Feng Gao Haijun Zang Xuewu Dai State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China China Railway Shenyang Group Co. Ltd Tongliao logistics center Shenyang China China Railway Shenyang Group Co. Ltd Dispatching office Shenyang China Department of Mathematics Physics and Electrical Engineering Northumbria University Newcastle upon Tyne UK

ISBN: (数字)9798350356618

ISBN: (纸本)9798350356625

This study focuses on optimizing urban rail transit operations during emergencies, aiming to reduce train traction energy consumption and expedite delay recovery by jointly optimizing arrival/departure times at each station and the operational trajectory between stations. A 3D STS (Space-Time-Speed) network is created to merge macroscopic train timetable scheduling with microscopic train operation trajectory optimization. By appropriately setting dimension resolutions, the system approximates the train's position, speed, and acceleration, transforming the complex train operation problem into a more manageable path planning challenge. Propose dual objectives: minimize net traction energy and delay time, aiming to reduce overall train operating costs and delays. Weighted summation combines objectives into a single nonlinear optimization. Dynamic programming then tackles the transformed path planning problem. The simulation results of Beijing Yizhuang Line show that while delay increases energy consumption, judicious selection of train operation trajectory can significantly reduce the energy consumption of the train. Factoring in energy consumption yields a 15.43% reduction compared to disregarding it, ensuring more efficient energy use without disrupting normal train operations.

关键词： Energy consumption Costs Three-dimensional displays Simulation Velocity control Delays Dynamic programming Time factors Resource management Trajectory optimization

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Data-Driven Dynamic Event-Triggered Sliding-Mode Heading Control for Unmanned Surface Vehicles with Uncertainties

Data-Driven Dynamic Event-Triggered Sliding-Mode Heading Con...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Huarong Zhao Jinjun Shan Xing Li Hongnian Yu School of Internet of Things Engineering Jiangnan University Wuxi P. R. China Department of Earth and Space Science and Engineering York University Toronto ON Canada School of Electrical Engineering and Intelligentization Dong-guan University of Technology Dongguan P. R. China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Liaoning P. R. China School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

This paper investigates a data-driven dynamic event-triggered sliding mode heading control problem for un-manned surface vehicles with uncertain dynamics models. First, a virtual sensor is introduced to establish a compact dynamic linearization model for the unmanned surface vehicle. Then, a dynamic event-triggered scheme is developed to alleviate the communication burden. Moreover, a sliding mode surface is designed, and a data-driven dynamic event-triggered sliding mode heading control approach is formulated. Finally, rigorous mathematical proofs are given, and several simulations demon-strate the effectiveness and superiority of the proposed method compared to existing approaches.

关键词： Uncertainty Event detection Soft sensors Delay effects Mathematical models Data models Steady-state Vehicle dynamics Autonomous vehicles Cybernetics

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Hexapod Robot Gait Switching Based on Different Wild Terrains

Hexapod Robot Gait Switching Based on Different Wild Terrain...

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Data Driven Control and Learning Systems (DDCLS)

作者： Shijie Fei Yiyang Chen Hongfeng Tao Hongtian Chen School of Mechanical and Electrical Engineering Soochow University Suzhou P. R. China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi P. R. China Department of Automation Shanghai Jiao Tong University Shanghai China

Hexapod robots have become an indispensable part of legged robots due to their excellent stability and traversability, and have recently become a hot research topic. In complex outdoor environments, the ability of the hexapod robot to switch its motion strategy according to the terrain is crucial for improving its mobility. This paper presents a terrain recognition network that enables our hexapod robot to switch its forward gait based on the different types of outdoor terrain. This method provides better stability for the hexapod robot than traditional single-gait walking through different terrains.

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Towards Energy-Efficiency: Integrating MATD3 Reinforcement Learning Method for Computational Offloading in RIS-Aided UAV-MEC Environments

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IEEE Internet of Things Journal 2025年

作者： Wu, Liangshun Zhang, Cong Zhang, Bin Du, Jianbo Qu, Junsuo Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai201210 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts & Telecommunications Xi'an710061 China Xinjiang University of Political Science and Law Tumushuke832003 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Department of Computer City University of Hong Kong 999077 Hong Kong School of Communications and Information Engineering Xi'an University of Posts & Telecommunications Xi'an710061 China

With the proliferation of IoT devices, there is an escalating demand for enhanced computing and communication capabilities. Mobile Edge Computing (MEC) addresses this need by relocating computing resources to the network edge, thereby delivering swifter and more efficient services. This paper introduces a computation offloading and energy consumption optimization framework that leverages Reconfigurable Intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and MEC. The scheme aims to maximize energy efficiency through the optimization of task allocation, RIS phase shifts, and UAV trajectories. By employing the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) reinforcement learning algorithm, the paper further refines UAV trajectories and RIS configurations. The simulation results indicate that the proposed method surpasses the traditional Concave-Convex Procedure (CCCP) algorithm in both UAV trajectory control and RIS configuration, demonstrating quicker convergence and enhanced stability. The method proves to be adaptable to diverse environments and tasks, showcasing notable benefits in RIS-assisted interference suppression, particularly with large RIS, thereby enhancing UAV data reception rates. Additionally, MATD3 exhibits faster and smoother convergence for extended task durations and smaller RIS scenarios. Simulation results reveal that UAVs tend to move closer to RIS, with energy efficiency falling as IoT tasks increase, affirming the proposed algorithm's high energy efficiency and effectiveness. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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