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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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Dynamic soft sensor modeling based on time series error compensation

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Huagong Xuebao/CIESC Journal 2010年第2期61卷 439-443页

作者： Du, Wenli Guan, Zhenqiang 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

Because static soft sensor modeling can not reflect the dynamic information of industrial processes, which lead to worse estimation precision and robustness. A dynamic soft sensor modeling based on least square vector machine(LS-SVM) and ARMA time series prediction modeling was presented. A static soft sensor model based on LS-SVM was established firstly, and then dynamic correction in the static model was made by using the dynamic estimation of prediction error in ARMA to improve the dynamic response characteristics. Finally, the proposed LSSVM-ARMA was used to predict the concentration of ethane in ethylene distillation. Simulation indicated that this method featured good approximation and good generalization ability as compared with LSSVM, and could be used in soft sensor. © All Rights Reserved.

关键词： Time series

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Object kinematic model: A novel approach of adaptive background mixture models for video segmentation

Object kinematic model: A novel approach of adaptive backgro...

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World Congress on Intelligent control and Automation (WCICA)

作者： Jin Yu Xuan Zhou Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China

In the field of video surveillance, adaptive Gaussian mixture model (GMM) is widely used as the background-pixel dynamic modeling approach. GMM produced each pixel Gaussian distribution corresponds to the respective, but this ignores the impact of the movement of the object itself. The ideas of object kinematic model is presented to guide the number of distribution in the process of iterative, which can speed up the process of clustering, and the results indicate that this method can improve the efficiency and stability of background modeling.

关键词： Hidden Markov models Adaptation model Pixel Kinematics Gaussian distribution Trajectory Analytical models

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Design and implementation of intelligent control system for propylene distillation column

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Huagong Xuebao/CIESC Journal 2010年第2期61卷 347-351页

作者： Wang, Zhenlei Ye, Zhencheng 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 State Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China

In this paper, a soft sensor technique on the basis of support vector machines (SVM) was proposed to estimate the propylene concentration on the bottom of the distillation column, which took into consideration of the process knowledge and operation characteristics of the propylene distillation column. The advantage of SVM in small samples modeling was taken in the soft sensor technique. Furthermore, an intelligent control system was designed to real-time control the bottom propylene concentration in the distillation. A fuzzy PID was used as the master controller for the propylene concentration. One PID controller was used as the slave controller for the sensitive plate temperature. The two controllers constituted a cascade control system. In order to eliminate disturbance of the feed stock, a feedforward controller was designed in the system. The designed soft sensor and control strategy were used in one selected olefin plant and the results were demonstrated and discussed in this paper. The results were promising and showed that the constructed soft sensor was precise enough to satisfy the industrial on-site requirements. Moreover, the control strategy was efficient to guarantee the bottom propylene concentration under the specified limit. © All Rights Reserved.

关键词： Distillation columns

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Multiple models robust adaptive control with reduced model

Multiple models robust adaptive control with reduced model

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2010 8th IEEE International Conference on control and Automation, ICCA 2010

作者： Liu, Jiazhen Wang, Zhenlei Wang, Xin Wang, Dahai Qian, Feng East China University of Science and Technology China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Center of Electrical and Electronic Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781424451951

The traditional robust adaptive control broadens the application of the routine adaptive control because of considering the uncertainty of the practice plant. However, traditional robust adaptive control solves the problem that the plant would be unstable under some uncertainties and it often ignores the dynamic property and steady-state property, which makes the traditional robust adaptive control unfit for practice plant, whose working condition changes randomly. To solve these problems, this paper designs multiple models robust adaptive controller for the plant which can be describeled by Autoregressive Moving Average (ARMA) model and with unmodeled dynamics. First, the normalization factor is used to convert the system unmodeled dynamic to bounded disturbance, and then, many fixed controller and two robust adaptive controllers are designed based on system reduced model according to the changing range of the working condition and the best controller computed by the performance index is chosen as the working controller. Simulation illustrates that the proposed method is preferable when there are unmodeled dynamics and changing working condition. © 2010 IEEE.

关键词： controllers

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Dynamic simulation of primary esterification section of poly(ethylene-terephthalate)

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Huagong Xuebao/CIESC Journal 2010年第8期61卷 1933-1941页

作者： Luo, Na Ye, Zhencheng Zhong, Weimin Qian, Feng School of Information Science and Engineering East China University of Science and Technology Shanghai 200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai 200237 China

Dynamic model is the basis of dynamic optimization in chemical process. In this paper a dynamic model for esterification section of poly(ethylene-terephthalate) (PET) was developed using segment method. Different from other researches, the model considered the interaction between esterification reactor and the column. Dynamic responses of process operating condition were analyzed with basic control strategies. Simulation results show that properties of products such as carboxyl end concentration, degree of polymerization response quickly to step change of feed molar ratio, reactor temperature, pressure and liquid level. Also these step changes significantly affected the changes in gas flow of ethylene glycol and water. control system plays a significant role in the stability of PET esterification process. © All Rights Reserved.

关键词： Polyethylene terephthalates

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Simulation of distillation unit based on artificial immune network multi-agent algorithm

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Huagong Xuebao/CIESC Journal 2010年第12期61卷 3186-3192页

作者： Shi, Xuhua 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 Research Institute of Electric Automatic Control Ningbo University Zhejiang Ningbo 315211 China

In petrochemical field, the process simulation for distillation is an important task. The key parameter in the distillation process simulation is the tray efficiency, which can not be obtained easily. Thus the determination of appropriate tray efficiency is an important issue. In this study, artificial immune network multi-agent optimization strategy(Maopt-aiNet), which combines immune mechanics and multi-agent technology, is used to determine the Murphree efficiency. The main search operators of Maopt-aiNet include neighborhood clonal selection, neighborhood competition, self-confidence motivation, self-confidence neighborhood learning, and neighborhood collaborative operators. Based on the process and analysis data of the distillation unit, Maopt-aiNet is applied to determine the Murphree efficiency for each stage and to minimize the square summation of model's analog relative error of the stage temperature. The experimental results show that with the tray efficiency determined by Maopt-aiNet the model fits the actual distillation unit fairly well. The method can be used to guide the operation of the distillation process. © All Rights Reserved.

关键词： Distillation

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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)

作者： Xu Bin Wang Honggang Qi Rongbin Qian Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai China Key Laboratory of Advanced Control East China University of Science and Technology Shanghai China

关键词： Cloning Algorithm design and analysis optimization Evolutionary computation Erbium Hypercubes Measurement

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Integration of multi-feature for moving target detection algorithm

Integration of multi-feature for moving target detection alg...

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International Conference on Electrical and control Engineering, ICECE 2010

作者： Yu, Jin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9780769540313

Moving object segmentation and marking object area is one of the key technologies of intelligent surveillance. In this paper, combining the background modeling in pixel level, the proposed algorithm presented gradient-based spatial characteristics in order to improve detection accuracy. For the trade-off problem of background modeling, established the velocity characteristics for each property of moving targets, to make online updates of the GMM more adaptable. The results indicate that this technique can improve the efficiency and stability of detection. © 2010 IEEE.

关键词： Economic and social effects

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