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Cascaded four-wave mixing all-optical wavelength converter based on highly nonlinear fiber deposited graphene oxide

Journal of Materials Science & Technology 2024年第4期171卷 10-15页

作者： Yuanhongliu Gao Xiaoyu Chen Tonglei Cheng Fang Wang Xin Yan College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyang 110819China

The all-optical wavelength conversion using cascaded four-wave mixing(FWM)phenomena with graphene oxide(GO)and a highly nonlinear fiber(HNLF)device is demonstrated *** has a strong third-order nonlinear effect and is an excellent nonlinear optical material for nonlinear optical wavelength *** group velocity matching of pump and signal,HNLF,and GO amplification promote the cascaded nonlinear frequency mixing *** the experimental and analytical results,the maximum spacing between signal and pump is 21 nm,and specifically,the order of cascaded FWM light increases from order 1 to order 2 with increasing GO,and the first-order FWM conversion effi-ciency increases to a maximum of−14.5 *** the best of our knowledge,this is the first time that cascaded FWM-based all-optical wavelength conversion in HNLF-GO with wide wavelength selectivity is investigated with combined pump and signal *** findings not only provide an effective method for achieving all-optical wavelength conversion in cascaded FWM but also offer the possibility of fabricating high-performance nonlinear optical devices.

关键词： Four-wave mixing Graphene oxide Highly nonlinear fiber Optical wavelength conversion

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Further results on quantized stabilization of nonlinear cascaded systems with dynamic uncertainties

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Science China(Information Sciences) 2016年第7期59卷 202-213页

作者： Tengfei LIU Zhong-Ping JIANG State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Department of Electrical and Computer Engineering Polytechnic School of Engineering New York University

This article studies the quantized partial-state feedback stabilization of a class of nonlinear cascaded systems with dynamic uncertainties. Under the assumption that the dynamic uncertainties are input-to-state practically stable, a novel recursive design method is developed for quantized stabilization by taking into account the influence of quantization and using the small-gain theorem. When the dynamic uncertainty is input-to-state stable, asymptotic stabilization can be achieved with the proposed quantized control law.

关键词： quantized control nonlinear systems dynamic uncertainties asymptotic stabilization

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Robust Adaptive Control Design for Rotorcraft Unmanned Aerial Vehicles Based on Sliding Mode Approach

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Transactions of Tianjin University 2014年第6期20卷 393-401页

作者：郭建川鲜斌 Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and AutomationTianjin University

This paper presents a nonlinear robust control design method for a generic rotorcraft unmanned aerial vehicle(RUAV). The control objective is to let the RUAV track some pre-defined time-varying position and heading trajectories. The proposed controller employs feedback linearization process to realize the dynamic decoupling control and applies adaptive sliding mode control to compensate for the parametric uncertainties and external disturbances. The global asymptotical stability is proved via stability analysis. Compared with the cascaded controller, the proposed controller demonstrates a superior tracking performance and robustness through numerical simulation in the presence of parametric uncertainties and unknown disturbances.

关键词： rotorcraft unmanned aerial vehicle (RUAV) nonlinear robust control sliding mode control parametricuncertainty wind gust disturbance

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Data-driven cooperative output regulation of multi-agent systems under distributed denial of service attacks

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Science China(Information Sciences) 2023年第9期66卷 5-20页

作者： Weinan GAO Zhong-Ping JIANG State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Department of Electrical and Computer Engineering Tandon School of Engineering New York University

This paper addresses an optimal, cooperative output regulation problem for multi-agent systems with distributed denial of service attacks and unknown system dynamics. Unlike existing studies, the proposed solution is essentially a learning-based control strategy such that one can obtain a distributed control policy with internal models through online data and analyze the resilience of closed-loop systems, both without the precise knowledge of system dynamics in the state-space model. The efficiency of the proposed methodology is validated using computer simulations.

关键词： cooperative output regulation adaptive dynamic programming learning-based control multi-agent systems cybersecurity

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Model predictive control of high moisture extrusion cooking

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Control engineering Practice 2025年 162卷

作者： TicǍ, Adrian Pinnamaraju, Vivek S. Stirnemann, Eric Windhab, Erich J. ETH Zürich Department of Health Science and Technology Laboratory of Food Process Engineering Schmelzbergstrasse 9 Zürich8092 Switzerland ABB Corporate Research Center ABB Global Industries and Services Pvt. Ltd. Industrial Area Hoodi Karnataka Bengaluru560048 India Planted Foods AG Engineering and Automation Kemptpark 32-34 Kemptthal8310 Switzerland

High Moisture Extrusion Cooking (HMEC) has become a promising technology for producing plant-based meat alternatives. By using HMEC, food manufacturers can create meat-like textures from plant proteins, offering a sustainable solution with reduced carbon footprint to consumers. However, at the current stage of development, the automation level in HMEC is insufficient to ensure operational autonomy, reliability, and product quality expected by industry demands. This paper presents a predictive control framework designed to transform experience-based handled HMEC into a more reliable process operation, improving its production performance and facilitating industrial up-scaling. The proposed control structure is hierarchical, comprising two layers. At the upper layer, a model predictive control (MPC) algorithm determines the optimal set-points for the controllers at the lower layer. The predictive framework is built on the existing HMEC control architecture and can be further extended to achieve fully optimized production. Leveraging linear dynamic models, the approach mainly focuses on the protein melt control aiming to enhance production performance by minimizing the tracking error of process quantities correlated to product quality. The practical feasibility of the designed control solution has been proven on a pilot-scale extruder. Validation results have shown improved operational stability and reproducibility, while effectively tracking set-points for consistent meat-like fibrous structure formation and desired textural characteristics. © 2025 The Authors

关键词： Model predictive control

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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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Simulation study on interaction coefficient of DEM in non-spherical large size (5-30 mm) coal particles

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Particuology 2020年第6期18卷 142-153页

作者： Daolong Yang Yanxiang Wang Jianping Li Qingkai Wang Yuntao Wang Yanting Yu School of Mechareonic Engineering Jiangsu Normal UniversityXuzhou 221116China State Key Laboratory of Process Automation in Mining&Metallurgy/Beijing Key Laboratory of Process Automation in Mining&Metallurgy Beijing 102600China School of Mechatronic Engineering China University of Mining and TechnologyXuzhou221116China

The pneumatic conveying system of coal particles can greatly reduce the dust and improve the environmental quality at underground mining workface and the surrounding of coal *** particle shape and the interaction coefficients between particles and the contact surface play important roles in the pneumatic conveying and CFD-DEM *** order to build the semblable shape models and obtain the accurate interaction coefficients of large coal particles,this article establishes the con tact model by the particle overlap method and describes the mathematical model of the shape characteristics for large coal *** particle models are simulated by adopting the multi-index mixed orthogonal *** accumulation density,the porosity and the error between simulation and experiment are taken as the indexes,and the particle models and the particle contact coefficients are taken as the orthogonal test *** a result,three more accurate particle models and their interaction coefficients are obtained,which provide the model basis for the pneumatic conveying of large coal particles.

关键词： Non-spherical particle DEM Particle shape Large size particle Orthogonal experiment

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Improved fast model migration method for centrifugal compressor based on bayesian algorithm and Gaussian process model

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Science China(Technological Sciences) 2018年第12期61卷 1950-1958页

作者： CHU Fei DAI BangWu LU NanNan MA XiaoPing WANG FuLi School of Information and Control Engineering China University of Mining and Technology State Key Laboratory of Integrated Automation for Process Industries Northeastern University

Design and operation optimization of centrifugal compressor are always based on an accurate prediction model, however, due to the short time operation and lack of data information, it is difficult to get an accurate prediction model of a new centrifugal compressor in time. This paper applies an improved fast model migration method(FMM method) to develop the model of the new centrifugal compressor. The method adapts a Gaussian process(GP) model from an old centrifugal compressor to fit a new and similar centrifugal compressor, and the adaptation is conducted by a scale-bias adjustment migration technology. In order to obtain the better estimated parameters of migration, Bayesian method, which takes the prior knowledge into consideration, is used in the sequential experiment. The approach is validated by a specific simulation bench. The results indicate that the applied approach can achieve a better prediction precision with fewer data of the new centrifugal compressor compared to pure GP method, and can model the new centrifugal compressor rapidly.

关键词： Bayesian centrifugal compressor Gaussian process model model migration performance prediction

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Behavior of a Logistic Map Driven by White Noise

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中国物理快报（英文版） 2009年第6期26卷 63-66页

作者： YANG Zheng-Ling GAO Yang GAO Yong-Tao ZHANG Jun School of Electrical Engineering and Automation Tianjin UniversityTianjin 300072 Tianjin Key Laboratory of Process Measurement and Control Tianjin300072

In the real world,every nonlinear system is inevitably affected by *** an example,a logistic map driven by white noise is *** previous studies which focused on the behavior under local parameters to find analytical results,we investigate the whole driven logistic *** a white noise driven logistic map,its nondivergent interval decreases with increasing white *** white noise does not change the equilibrium point and two-cycle intervals in statistics,if the driven logistic map is kept *** particular,chaos can be excited by white noise only after the four-cycle bifurcation *** latest result is a necessary condition which has not been given in the literature[*** 18 (2008) 509],and it can be deduced from Sharkovsky's *** simulations prove these analytical results.

关键词： No English Keywords

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3D reconstruction of single rising bubble in water using digital image processing and characteristic matrix

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Particuology 2013年第2期11卷 170-183页

作者： Yuchen Bian Feng Dong Weida Zhang Hongyi Wang Chao Tan Zhiqiang Zhang Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and AutomationTianjin University School of Electrical Engineering and Automation Tianjin Polytechnic University

Reconstructing the shape of a bubble will lay a firm foundation for further description of the dynamic characteristics of bubbly flow, especially for a single rising bubble or separate bubbles whose interaction could be neglected. In this case, the rising bubble is usually simulated as an ellipsoid consisting of two semi-eUipsoids up and down. Thus the projected image of a bubble consists of two semi-ellipses. In this paper, a method for reconstructing the ellipsoid bubble model is described following digital image processing, using the Hough transform in 2D ellipse parameter extraction which could cover most of the bubble edge points in the image. Then a method based on characteristic symmetric matrix is described to detect 3D bubble ellipsoid model parameters from 2D ellipse parameters of projection planes. This method can be applied to bubbles rising with low-velocity in static flow field much in conformity with the projection theory and the shape variation of the rising bubble. This method does not need to solve nonlinear equation sets and provides an easy way to calculate the characteristic matrix of a space ellipsoid model for deformed bubble. For bubble application, two assumed conditions and a calibration factor are proposed to simplify calculation and detection. Errors of ellipsoid center and three axes are minor. Errors of the three rotation angles have no negative effect on further study on bubbly flow.

关键词： Bubble Digital image processing Parameter extraction Ellipsoid model Reconstruction Characteristic matrix

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