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Dynamic soft sensor modeling based on time series error compensation

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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Improved differential evolution algorithm used for load distribution of hot strip rolling

Improved differential evolution algorithm used for load dist...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Feng, Yao Weidong, Yang School of Information Engineering University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781424464388

To solve the problem that standard differential evolution algorithm is easy to premature convergence, here gives a new variant form-self-disturbance variation, and takes some improvement to it. New mutation could maintain the diversity of population, and the improvement could increase convergence speed. The improved method achieves performance improvement, and does not increase the time complexity of the original algorithm. Then, it is applied to the calculation of hot rolling load distribution. © 2010 IEEE.

关键词： Hot rolling

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Analysis and pattern recognition of blast furnace burden surface based on multi-radar data

Analysis and pattern recognition of blast furnace burden sur...

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2010 International Conference on Intelligent control and Information processing, ICICIP 2010

作者： Zhou, Xiang Li, Xiaoli Liu, Dexin Yin, Yixin Chen, Xianzhong Hou, Qingwen Department of Automation Information and Engineering School University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing Beijing 10083 China

ISBN: (纸本)9781424470488

Iron making is the first stage and also an important part in steel making process, which will bring the problem of energy efficiency and economic benefits. In this process, the distribution of the blast burden impacts greatly on the production of BF (blast furnace). Therefore, the prediction of furnace burden distribution in furnace throat will play an important role in the control strategy of furnace burden. Based on the data from the multi-radar, the blast burden curve can be formed. Feature extraction and classification based on different curves (i.e. different pattern) can be made by using BP neural networks. The work proposed in this paper will be a guidence for the future research of burden surface based on the data of phased-array radar. © 2010 IEEE.

关键词： Blast furnaces

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Application of fuzzy pattern recognition in burden surface identification

Application of fuzzy pattern recognition in burden surface i...

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2010 International Conference on Intelligent control and Information processing, ICICIP 2010

作者： Liu, Dexin Li, Xiaoli Zhou, Xiang Yin, Yixin Chen, Xianzhong Hou, Qingwen Department of Automation Information and Engineering School University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education University of Science and Technology Beijing Beijing 10083 China

ISBN: (纸本)9781424470488

A kind of pattern recognition method with Fuzzy clustering is applied to identify the burden surface of blast furnace. According to the information of burden surface distribution, the target clustering analysis is used to set up a standard model database. Based on the character of distribution, each target burden surface is matched into different standard model database by using fuzzy pattern recognition method. Maximal minimal similarity method is adapted in the course of fuzzy pattern recognition. The simulation results show the effectiveness of the proposed method. © 2010 IEEE.

关键词： Blast furnaces

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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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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

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.

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

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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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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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The time series soft-sensor modeling based on Adaboost_LS-SVM

The time series soft-sensor modeling based on Adaboost_LS-SV...

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World Congress on Intelligent control and Automation (WCICA)

作者： W.-L. Du Z.-Q. Guan Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

With regards to the petrochemical processes with various operating states and dynamic performance which will affect estimation precision for the static soft sensor, a time series soft sensor model which uses the time series of process variables to estimate the dynamic performance of quality variable was proposed. Meanwhile, the integrated Adaboost learning algorithm is introduced. With the help of this method, training samples and modeling for several times, according to the modeling error to renew the next sample data, in order to obtain a series of different basic models. Every basic model will be weighted in the last step; as a result, a more precise combined LS-SVM model will be established. According to the prediction of benzene content of column reactor in the azeotropic rectification tower, the effectiveness of the method is demonstrated.

关键词： Support vector machines Time series analysis Data models Chemical industry Estimation process control Heuristic algorithms

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Dynamic optimization with an improved θ-PSO based on memory recall

Dynamic optimization with an improved θ-PSO based on memory...

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World Congress on Intelligent control and Automation (WCICA)

作者： Weimin Zhong Jianliang Xing Yi Liang Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

A comparative study of θ-PSO and its improved model with partial particles randomization strategy on their abilities of tracking extrema in dynamic environments was carried out in our earlier work. And the results shown that θ-PSO has better performance in dynamic optimization than standard PSO. In this paper, an improved θ-PSO with memory recall and varying scale randomization strategy (θ-PSO-MR) is put forward. The eligible memory particles are recalled when the landscape changes. And the vary scale randomization is introduced through the evolution to maintain the swarm diversity. The offline error in the non-trivial multimodal dynamic functions MPB indicates that this improved θ-PSO deals well with the complex dynamic tracking and optimization. And in some cases, θ-PSO-MR outperforms θ-PSO-Rn for the introduction of memory recall.

关键词： optimization Particle swarm optimization Heuristic algorithms IEEE services Laboratories

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