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第三十四届中国控制会议

作者： TANG Yang DU Wei The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology The Institute of Textiles and Clothing The Hong Kong Polytechnic University

ISBN: (纸本)9781467374439

This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain,in which uncertainties in determination of driver nodes and control gains are considered. A framework by including interval uncertainties is proposed for robust controllability. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affect the controllability of neuronal networks.

关键词： Synchronization,Neuronal networks,controllability,Robustness,Multiobjective optimization

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Co-simulation Research of Autonomous Landing control System 33

Co-simulation Research of Autonomous Landing Control System

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第三十三届中国控制会议

作者： WANG Zhaoning WU Shengxi DUN Xiangming GU Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Research Institute of Robotics Shanghai Jiao Tong University

ISBN: (纸本)9781479947249

In this paper, a control simulation of the autonomous landing process of a Vertical Take-Off and Landing(VTVL) Reusable Launch Vehicle(RLV) is proposed and we consider the effects of the inner liquid propellant sloshing, elastic vibration, disturbance force, disturbance torque and other complex conditions in the virtual RLV model. On the basis of dynamics modeling of the RLV, we analyzed RLV's landing process. The landing control system was designed under certain conditions. Co-simulation Research was achieved by ADAMS and MATLAB/Simulink. The simulation results show that the control system performs well.

关键词： vertical take-off and landing autonomous landing reusable launch vehicle control system co-simulation research

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Feedback control for Uncertain Networked control Systems with Random Input Time Delay 28

Feedback Control for Uncertain Networked Control Systems wit...

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第28届中国控制与决策会议

作者： Qiu Chuanxu Wen Jiwei Peng Li Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan University

ISBN: (纸本)9781467397155

This paper is concerned with the feedback control problem for a class of uncertain networked control systems with random input time *** random delay is modeled as a Markov process while the uncertainties are time varying but *** employing a new stochastic lyapunov function and transferring the original random system into a singular form,which has the same mean square stability,sufficient stable and stabilizable conditions for the underlying systems are derived via a Lyapunov-Krasovskii functional ***,a numerical example is given to illustrate the main results.

关键词： Uncertain networked control systems Random delay Markov process

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Distributed predictive control for energy management of multi-microgrids systems

Distributed predictive control for energy management of mult...

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13th IFAC Symposium on Large Scale Complex Systems: Theory and Applications, LSS 2013

作者： Xu, Jun Zou, Yuanyuan Niu, Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China Univ. of Science and Technology Shanghai 200237 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

In this paper, a distributed model predictive control (DMPC) scheme is presented to optimize the power flow management of microgrids in smart grid environment. For a multi-microgrids system in which local microgrid links with each other through particular channels for power and information, the proposed method can maximize the overall energy efficiency. The DMPC optimization problem is formulated by minimizing the surplus/insufficient energy in each microgrid and a constraint restriction is imposed to guarantee the closed-loop stability. A simulation example is carried out to demonstrate the feasibility and effectiveness of this energy management strategy. © IFAC.

关键词： Electric power distribution

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Sampled-Data Consensus of First-Order Multi-Agent Systems with Delayed-State-Derivative Feedback

Sampled-Data Consensus of First-Order Multi-Agent Systems wi...

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第25届中国控制与决策会议

作者： Na Wang Zhihai Wu Li Peng The Key Laboratory for Advanced Process Control of Light Industry of the Ministry of Education School of Internet of Things Engineering Jiangnan University

ISBN: (纸本)9781467355339

This paper is concerned with sampled-data consensus of first-order delayed multi-agent systems with delayed-state-derivative feedback. First, the delay decomposition technique is used for obtaining the consensus protocol based on sampled-data. Then, the stability theory of linear systems and the algebra graph theory are employed to derive the necessary and sufficient conditions about the sampling period guaranteeing the achievement of consensus. Last, simulations are provided to demonstrate the effectiveness of the theoretical results.

关键词： Multi-Agent Systems Consensus Delayed-State-Derivative Feedback Sampled-Data

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Simulation and Analysis on Multiple Steady States of an Industrial Acetic Acid Dehydration System

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Chinese Journal of chemical Engineering 2011年第6期19卷 983-989页

作者：李绍军黄定伟 Key Laboratory of Advanced Control and Optimization for Chemical Processes （East China University of Science and Technology） Ministry of Education Shanghai 200237 China

In this work, an industrial acetic acid dehydration system via heterogeneous azeotropic distillation is simulated by Aspen Plus software. Residue curves are used to analyze the distillating behavior, and appropriate operating region of the system is determined. Based on steady states simulation, a sensitivity analysis is carried out to detect the output multiple steady states in the system. Different solution branches are observered when the flow rates of the feed stream and the organic reflux stream are selected as manipulated variables. The performance of the column under different steady states is different. A method is oroposed to achieve the desired steady state.

关键词： acetic acid dehydration heterogeneous azeotropic distillation residue curve multiple-steady states

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Isobaric Vapor-Liquid Equilibrium of Binary Systems： p-Xylene ＋（Acetic Acid, Methyl Acetate and n-Propyl Acetate） and Methyl Acetate ＋ n-Propyl Acetate in an Acetic Acid Dehydration process

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Chinese Journal of chemical Engineering 2013年第2期21卷 171-176页

作者： HUANG Xiuhui ZHONG Weimin PENG Changjun QIAN Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The vapor-liquid equilibrium data of four binary systems (acetic acid +p-xylene, methyl acetate +n-propyl acetate, n-propyl acetate +p-xylene and methyl acetate +p-xylene) are measured at 101.33 kPa with Ellis equilibrium still, and then both the NRTL and UNIQUAC models are used in combination with the HOC model for correlating and estimating the vapor-liquid equilibrium of these four binary systems. The estimated binary VLE results using correlated parameters agree well with the measured data except the methyl acetate +p-xylene system which easily causes bumping and liquid rushing out of the sampling tap due to their dramatically different boiling points. The correlation results by NRTL and UNIQUAC models have little difference on the average absolute deviations of temperature and composition of vapor phase, and the results by NRTL model are slightly better than those by UNIQUAC model except for the methyl acetate +n-propyl acetate system, for which the latter gives more accurate correlations.

关键词： vapor-liquid equilibrium p-xylene acetic acid methyl acetate n-propyl acetate parameter correlation

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Support Vector Regression based Spectral Calibration Model Building for In-situ process Measurement via Near-infrared Spectroscopy 41

Support Vector Regression based Spectral Calibration Model B...

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第41届中国控制会议

作者： Xiaoyu Qu Tao Liu Yang Wu Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Institute of Advanced Control Technology Dalian University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For in-situ measurement of biochemical process variables such as the multi-component concentrations of a fermentation process via near-infrared spectroscopy,an improved spectral calibration model building method is proposed in this paper,based on the support vector regression(SVR) in combination with a grey wolf optimizer for parameter *** address the nonlinear properties and high-dimensional problem of infrared spectral variables,the Gaussian kernel function is adopted to establish an SVR based spectral calibration model so as to improve fitting accuracy with respect to the training ***,a grey wolf optimization algorithm is given to determine the model parameters for obtaining good prediction *** application to a fluidized bed drying(FBD) process for prediction of moisture content and another lactic acid fermentation process for multi-component prediction are performed,well demonstrating the effectiveness and superiority of the proposed modelling method over the traditional partial least-squares modeling algorithms.

关键词： spectral calibration model near-infrared spectroscopy in-situ measurement support vector regression(SVR) grey wolf optimizer multi-component prediction

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Robust multi-layer extreme learning machine using bias-variance tradeoff

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Journal of Central South University 2020年第12期27卷 3744-3753页

作者： YU Tian-jun YAN Xue-feng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and TechnologyShanghai 200237China

As a new neural network model,extreme learning machine(ELM)has a good learning rate and generalization ***,ELM with a single hidden layer structure often fails to achieve good results when faced with large-scale multi-featured *** resolve this problem,we propose a multi-layer framework for the ELM learning algorithm to improve the model’s generalization ***,noises or abnormal points often exist in practical applications,and they result in the inability to obtain clean training *** generalization ability of the original ELM decreases under such *** address this issue,we add model bias and variance to the loss function so that the model gains the ability to minimize model bias and model variance,thus reducing the influence of noise signals.A new robust multi-layer algorithm called ML-RELM is proposed to enhance outlier robustness in complex *** results show that the method has high generalization ability and strong robustness to noise.

关键词： extreme learning machine deep neural network robustness unsupervised feature learning

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A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in chemical Engineering

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Chinese Journal of chemical Engineering 2011年第2期19卷 299-307页

作者：杨传鑫颜学峰 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

Considering that the performance of a genetic algorithm （GA） is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm （FAGA） combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex *** FAGA,immune theory is used to improve the performance of selection ***,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control *** experi-ments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy ***,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.

关键词： fuzzy logic controller genetic algorithm artificial immune system reaction kinetics model

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