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Gaussian process assisted coevolutionary estimation of distribution algorithm for computationally expensive problems

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Journal of Central South University 2012年第2期19卷 443-452页

作者： Luo, Na Qian, Feng Zhao, Liang Zhong, Wei-min Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China

In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.

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Modified Self-adaptive Immune Genetic Algorithm for optimization in the Combustion Side Reaction of p-Xylene Oxidation

Modified Self-adaptive Immune Genetic Algorithm for Optimiza...

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第23届过程控制会议

作者： Lili Tao Xiangdong Kong Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E Automation Institute East China University of Science and Technology Shanghai 200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E

In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution of non-linear optimization problems encountered in many engineering applications. In IGA, the mutation factor values are either fixed or change together according to a function of the individual’s current generation number during all the search process. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. A modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to strengthen the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method can quickly converge to the global optimum and overcome premature problem. Then, this algorithm is applied to optimize a feed forward neural network to measure the content of products in the combust ion side reaction of p-xylene oxidation, and satisfactory results are obtained.

关键词： Self-adaptive immune genetic algorithm Artificial neural network Measurement p-Xylene oxidation process

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Peak Traffc Forecasting Using Nonparametric Approaches

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Journal of Shanghai Jiaotong university(Science) 2012年第1期17卷 76-81页

作者：张扬王梦灵 Shanghai Municipal Transportation Information Center Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

States of traffic situations can be classified into peak and nonpeak periods. The complexity of peak traffic brings more difficulty to forecasting models. Travel time index （TTI） is a fundamental measure in transportation. How to master the characteristics and provide accurate real-time forecasts is essential to intelligent transportation systems （ITS）. Cooperating with state space approach, least squares support vector machines （LS- SVMs） are investigated to solve such a practical problem in this paper. To the best of our knowledge, it is the first time to apply the technique and analyze the forecast performance in the domain. For comparison purpose, other two nonparametric predictors are selected because of their effectiveness proved in past research. Having good generalization ability and guaranteeing global minima, LS-SVMs perform better than the others. Providing sufficient improvement in stability and robustness reveals that the approach is practically promising.

关键词： traffic forecasting peak traffic nonparametric techniques

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Weighted least square support vector machine integrated with parameter optimization and its application in chemical process

Weighted least square support vector machine integrated with...

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International Conference on Natural Computation (ICNC)

作者： Wen-Tong Cui Xue-Feng Yan Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China

Considering that outliers can disrupt the correlation structure of least square support vector machine (LS-SVM), and that the parameters of LS-SVM play an important role in the performance, a novel weighted least square support vector machine integrated with parameter optimization is proposed to obtain the optimal parameters and to eliminate the effect of outliers. Several LS-SVM variants are applied in simulation experimentation and chemical process respectively to demonstrate the satisfactory performance of the proposed method.

关键词： optimization Training Support vector machines Oxidation Adaptation models Mathematical model Educational institutions

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A particle filter based on a constrained sampling method for state estimation

A particle filter based on a constrained sampling method for...

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15th International Conference on Information Fusion, FUSION 2012

作者： Zhao, Zhonggai Huang, Biao Liu, Fei Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi 214122 China Department of Chemical and Materials Engineering University of Alberta Edmonton AB T6G 2G6 Canada

ISBN: (纸本)9780982443859

Increasingly in practical applications, nonlinearity, non-Gaussianity, and constraint are considered when dealing with state estimation problems. This paper proposes a novel constrained particle filter (PF) approach for state estimation, where three constraint strategies are implemented: First, to ensure the validity of prior, prior particles are restrictedly sampled in the constraint region by a constrained inverse transform sampling method. Second, if constraints are imposed on the posterior, a constrained re-sampling method, similar to the existing acceptance/rejection constrained PF method, is proposed to restrict the posterior particles to be generated from the valid prior particles. Third, the validity of state estimation is ensured through adjustment of part of posterior particles according to the posterior density function of states, which is accomplished by deleting uniformly selected violated posterior particle and uniformly selected valid posterior particle for reproduction. Compared with the existing methods, the proposed method implements constraints with better physical interpretation, and involves no numerical optimization procedure and no restrictive assumptions about the distributions. Simulation results demonstrate its effectiveness. © 2012 ISIF (Intl Society of Information Fusi).

关键词： State estimation

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Energy consumption monitoring of the steam pipe network based on affinity propagation clustering

Energy consumption monitoring of the steam pipe network base...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xiazhu You Wenli Du Liang Zhao Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The steam system is an important part of chemical utility system, but there are widespread phenomenon about lack of testing information, energy consumption configuration depend on given experience and wasting energy. So this paper puts forward a method about the steam pipe network system's status identification of different energy consumption based on the steam pipe network's characteristics of complex structure, much steam equipment, lack of testing information and difficult to build accurate mathematical model. The method based on affinity propagation clustering that can solve big set of data's clustering problem quickly and effective. As it is hard to find preference parameters and damping factor, this paper uses PSO to find the most optimal parameters in order to achieve the best clustering effect. This method is applied test both in classic data set and the steam pipe network of ethylene plant's status identification, the results show the effectiveness of this method.

关键词： Energy consumption Indexes optimization Clustering algorithms Temperature measurement Pattern recognition Frequency modulation

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Simulation and optimization of acetylene converter with decreasing catalyst activity

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Huagong Xuebao/CIESC Journal 2012年第1期63卷 185-192页

作者： Tian, Liang Jiang, Da Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China Olefins Department SINOPEC Shanghai Petrochemical Company Limited Shanghai 200540 China

Since the activity and selectivity of acetylene hydrogenation catalyst change with time, the operating parameters need to be changed to maximize the profit. Therefore, we collected the industrial process data and estimated the parameters of kinetic model and deactivation model by genetic algorithm. We compared the selectivity and activity performance of two commonly used catalysts. For two reactors in series filled with different catalysts, we proposed the methods of combinatorial optimization and ratio assignment to optimal ethylene production rate. When these optimization strategies were implemented in the actual plant, ethylene production rate and the total selectivity increased significantly. © All Rights Reserved.

关键词： Combinatorial optimization

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Kinetics of COx formation in the homogeneous metal/bromide-catalyzed aerobic oxidation of p-xylene

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International Journal of chemical Kinetics 2012年第5期44卷 277-283页

作者： Sun, Weizhen An, Meiying Zhong, Weimin Zhao, Ling State Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The homogeneous metal/bromide-catalyzed aerobic oxidation of p-xylene with different catalyst concentrations was carried out, and the formation kinetics of COx including CO2 and CO was measured. The simplified elementary steps for the formation of COx were summarized, on the basis of which the kinetic model of COx formation was established. The model calculations were in good agreement with the experimental data for the CO2 formation and also successfully captured the first peak of the CO formation rate as a function of time. The obtained rate constants have narrow confidence intervals, among which only k1 and k2 are the adjustable parameters for different catalyst conditions. The decarboxylation of the carboxyl group in aromatic acid, the oxidation of the aryl radical, and the destruction of acetic acid are the major sources of CO2. The formation of CO mainly results from the destruction of acetic acid and the oxidation of the aryl radical. Copyright © 2012 Wiley Periodicals, Inc.

关键词： Acetic acid

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Sliding mode control for linear uncertain switched systems

Sliding mode control for linear uncertain switched systems

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Chinese control Conference (CCC)

作者： Yonghui Liu Yugang Niu Daniel W. C. Ho Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China Department of Mathematics City University of Hong Kong Kowloon Hong Kong China

ISBN: (纸本)9781467325813

This paper considers the problem of sliding mode control (SMC) for a class of linear uncertain switched systems. In the controlled systems, it is not required that each subsystem model shares the same input channel, which is usually assumed in some existing works. By means of a transformation on input matrices, a single integral sliding surface is designed and the switching signals depending on the average dwell time are given. It is shown that the designed sliding mode controller can guarantee the reachability of the sliding surface. Moreover, the sliding motion on the specified integral sliding surface is exponentially stable under the designed switching signal. The efficiency of the proposed method is demonstrated by a simulation.

关键词： Switches Switched systems Stability analysis Sliding mode control Power system stability Linear systems

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Quantized H∞ control for networked control systems with multiple packet dropouts

Quantized H∞ control for networked control systems with mul...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Zhenzhen Su Huaicheng Yan Hao Zhang Jiujun Cheng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Electronics and Information Engineering Tongji University Shanghai 200092 China

This paper is concerned with the problem of quantized H∞ control for networked control systems (NCSs) with multiple packet dropouts. A new model is given to describe the systems with the input and output quantization and multiple packet dropouts. Both the multiple measurement and control packet dropouts are described by two binary switching sequences that obey certain conditional probability distribution. An observer-based controller is designed to ensure the exponentially mean-square stable of the closed-loop system and to guarantee an optimal H∞ disturbance attenuation level. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.

关键词： H∞ control Networked control Systems Multiple Packet Dropouts Quantization

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