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Soft-sensing of turbine steam flow based on CQGAPSO

Huagong Xuebao/CIESC Journal 2010年第11期61卷 2855-2860页

作者： Tang, Qifeng Zhao, Liang Qi, Rongbin 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

Turbine steam flow is an important parameter for analyzing turbine operating efficiency. In order to solve such problems as lack of detection information, poor reliability of traditional measurement method, high cost and difficult installation of non-contact measurement method etc., a soft-sensing model based on the cooperative quantum genetic algorithm particle swarm optimization(CQGAPSO) and a well-defined part-connected neural network(NN) was proposed. It could eliminate some adverse effects of approximation ability caused by redundant structure of NN. The amplitude-based coding method and cooperation mechanism improved the learning efficiency, approximation precision and generalization of NN. The soft-sensing experimental results of turbine steam flow showed that the soft-sensing model of turbine steam flow could obtain higher prediction accuracy and greater robustness than the all-connection NN and other models. © All Rights Reserved.

关键词： Steam turbines

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Differential evolution inspired clone immune multi-objective optimization algorithm

Differential evolution inspired clone immune multi-objective...

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International Conference on Electrical and control Engineering, ICECE 2010

作者： Xu, Bin Wang, Honggang Qi, Rongbin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education School of Information Science and Technology East China University of Science and Technology NO 130 Meilong Road 200237 Shanghai China

ISBN: (纸本)9780769540313

This paper proposes a novel multi-objective optimization algorithm: differential evolution inspired clone immune multi-objective optimization algorithm (DECIMO). The novel algorithm uses a space-filling experimental design named symmetric Latin hypercube design (SLHD) to initialize the population which can obviously improve the uniformity of the individual distribution. A permutation of population individual indexes is generated and then a neighborhood for each population individual is defined according to the permutation. A differential evolution inspired neighborhood recombination operator, which based on the neighbors of each population member, is proposed to balance the exploration and exploitation abilities of the algorithm with no compromise of efficiency. The DE inspired operator is then invoked into the clone immune algorithm (CIA) to solve multi-objective problems (MOPs). We compare the proposed algorithm with NSGA2 and SPEA2 by executing it to 5 famous test functions. The results show that the proposed algorithm can fast converge to the global Pareto front and also can sustain a very uniform distribution. It is a potential algorithm for solving MOPs. © 2010 IEEE.

关键词： Multiobjective optimization

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Automatic spike detection based on real-time multi-channel template

Automatic spike detection based on real-time multi-channel t...

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Ji, Zhanfeng Wang, Xingyu Sugi, Takenao Goto, Satoru Nakamura, Masatoshi Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai China Department of Advanced Systems Control Engineering Saga University Saga Japan Research Institute of Systems Control Saga University Saga Japan

ISBN: (纸本)9781424493524

Automatic EEG spike detection provide valuable information for diagnosis of epilepsy. In the past 30 years, a number of algorithms were proposed. However, the basic idea of most algorithms is to identify spike activities. We have developed an algorithm based on identify non-spike activities for off-line analysis. In this paper, we improved the algorithm for online application using real-time template. Template method is a typical spike detection method. It was not widely employed because of the difficulty of making template. Our results suggested that multi-channel template is meaningful and effective for real-time detection. Spike activities can be detected with a delay of about 2 s. We also designed an simple user-friendly monitor interface for monitor and review spike events in real-time. © 2011 IEEE.

关键词： multi-channel template real-time spike detection Spike spike spikes jigs(templates) Real time algorithms MONITOR analysis of flowline

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Gross Error Detection and Data Reconciliation using Historical Data

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Procedia Engineering 2011年 15卷 55-59页

作者： Shaochao Sun Dao Huang Yanxue Gong Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Ecust shanghai 20037 China

With the information technology applied widely to process industry, a large amount of historical data which could be used for obtaining the prior probabilities of gross error occurrence is stored in database. To use the historical data to enhance the efficiency of gross error detection and data reconciliation, a new strategy which includes two steps is proposed. The first step is that mixed integer program technique is incorporated to use the prior information to detect gross errors. The second step is to estimate all detected gross errors and adjust process data with material, energy, and other balance constrains. In this step an improved method is proposed to achieve the same effect with traditional method through adjusting the covariance matrix. Novel prior information criteria are described and performance of this new strategy is compared and discussed by applying the strategy for a challenging test problem.

关键词： data rectification gross error detection mixed integer program projection matrix historical data

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Evolutionary algorithm based on the evolution of Pareto archive and individual migration

Evolutionary algorithm based on the evolution of Pareto arch...

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作者： Qi, Rongbin Ma, Tianyi Sun, Fan Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Shanghai Business School Shanghai China

An evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed, which is not only suitable for solving multi-objective optimization, but also effective for multimodal function. For each single objective population, single objective evolutionary algorithm is applied to optimize separately each of multi-objective functions, where individuals generated by tournament selection from the union of single objective and Pareto Archive population form the single objective population of next generation. Especially, individuals in Pareto archive population also join evolutionary operations. Simulations manifest that the proposed method can realize the search from multiple directions to obtain the non-dominated solutions scattered more uniformly over the Pareto frontier with better convergence metric compared to well-known NSGA-II algorithm. Individual migration from Pareto archive population by tournament selection is also proved to have the advantage in improving the converging speed and converging precision. Moreover, for multimodal single objective function, simulations also show that ideal optimizing solution can be obtained by properly separating single objective function into multi-objective function and applying the above method. © 2011 Zhejiang University.

关键词： Evolutionary algorithms

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Prediction of Cracking Gas Compressor Performance and Its Application in Process optimization

Prediction of Cracking Gas Compressor Performance and Its Ap...

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第23届过程控制会议

作者： Shaojun Li Feng Li Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of

In ethylene plant, charge gas compressor is one of the most important units. The charge gas compressor usually is a centrifugal compressor. The information of centrifugal compressors’ performance is not applicable to all of the conditions, which restricts the operation optimization of the compressor. To solve this problem, a tri-layer BP neural network was introduced to model the performance of compressor by using the data provided by manufacturers. The input data of the model in other conditions should be corrected according to the similar theory. At last, the method was used to optimize the system of charge gas compressor by embedding compressor performance model into the ASPEN PLUS model of compressor. The result shows that it is an effective method to optimize the compressor system.

关键词： Compressor characteristic curve neural-network modeling

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Method for coloring night-vision imagery based on multispectral semantic segmentation

Method for coloring night-vision imagery based on multispect...

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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Zhang, Weiwen Gu, Xiaojing Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781538666173

Color night vision can map natural colors to nighttime images of multiple bands (e.g., visible and long-wave infrared (LWIR)). These colors can assist the observers in better and faster understanding images, thus improving their situational awareness and shortening the reaction time. In this paper, we present an effective method combining deep learning and category colors. It utilizes the semantic segmentation for image segmentation first, and then colorize the image according to categories to avoid the same color scheme and unnatural colors. We compare our method with some others quantitatively and qualitatively, such as global colorization by single lookup table, where we show significant improvements. In addition, it can be expanded according to different environments and applications because of the fixed category colors. © 2018 IEEE.

关键词： Color

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Synchronization of Nonlinear Coupled Networks with Time-delay via Distributed Impulsive control

Synchronization of Nonlinear Coupled Networks with Time-dela...

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第三十二届中国控制会议

作者： ZHANG Hao FENG Gang YAN Huaicheng CHEN Qijun Department of Control Science and Engineering Tongji University Department of Mechanical & Biomedical Engineering City University of Hong Kong Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781479900305

In this paper,the synchronization of a nonlinear network with time-varying coupling delay is investigated via distributed impulsive *** objective is to design the distributed impulsive controller with minimum coupling strength such that the nonlinear network with coupling delay is globally exponentially *** sufficient conditions have been derived based on Lyapunov-Razumikhin method in terms of matrix *** example is presented to illustrate the effectiveness of the proposed control methods.

关键词： Global exponential synchronization Distributed impulsive control Time-varying delay Coupled network

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An application of the improved hybrid particle swarm optimization method in the gasoline blending process

An application of the improved hybrid particle swarm optimiz...

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International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011

作者： Shu, Yue Cheng, Hui Liu, Yi Qi, Rongbin Liu, Zhao 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 SinoPec Jinling Petrochemical Ltd. Nanjing 210033 China

In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline blending process. In addition, the proposed method has been applied onsite in a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and decrease the quality giveaways and blending cost significantly.

关键词： Genetic algorithms

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Stability analysis and stabilization of semi-Markov jump linear systems with unavailable sojourn-time information

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Science China(Information Sciences) 2024年第7期67卷 211-223页

作者： Xiaotai WU Yang TANG Shuai MAO Ying ZHAO School of Mathematics and Physics Anhui Polytechnic University Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.

关键词： semi-Markov chain semi-Markov jump linear systems σ-error mean square stability unavailable sojourn-time information

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