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Zoning search using a hyper-heuristic algorithm

Science China(Information Sciences) 2019年第9期62卷 193-195页

作者： Qinqin FAN Ning LI Yilian ZHANG Xuefeng YAN Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai Jiao Tong University Logistics Research Center Shanghai Maritime University Key Laboratory of Marine Technology and Control Engineering Ministry of CommunicationsShanghai Maritime University Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Dear editor,With the development of high-performance computing techniques, run time of meta-heuristic algorithms can be reduced effectively. However, improved computation power has not been indirectly converted into search capability in most of previous studies [1]. Moreover, the solution precision of an optimization problem is directly determined

关键词： pro CEC Zoning search using a hyper-heuristic algorithm

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Quantized H∞ control for networked systems with randomly multi-step transmission delays

Quantized H∞ control for networked systems with randomly mu...

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作者： Zhang, Yilian Yang, Fuwen Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

ISBN: (纸本)9781479940325

In this paper, a quantized H∞ control problem for networked control systems (NCSs) subject to randomly multi-step transmission delays is investigated. A quantizer is used before the measurement signal enters the communication network and the randomly multi-step transmission delays which are described by a mathematical model are considered during the transmission through the network. Sufficient conditions are derived for the considered system to satisfy the H∞ norm constraint subject to the randomly multi-step transmission delays. Simulation results demonstrate the effectiveness of the proposed method. © 2014 IEEE.

关键词： Networked control systems

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control Performance Assessment of Multivariable System Based on Multi-time-variant-disturbances Mixing GMV Method 29

Control Performance Assessment of Multivariable System Based...

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第29届中国控制与决策会议

作者： Yupeng Du Zhenlei Wang Xin Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Center of Electrical & Electronic Technology Shanghai Jiao Tong University

ISBN: (纸本)9781509046584

The disturbance in chemical process is complex and has the multiple characteristics,and the control performance assessment of multivariable system with multiple disturbances is one of the hot *** this paper,the control performance assessment method of multivariable systems,based on multi-time-variant-disturbances mixing generalized minimum variance(MMGMV),is ***,the generalized minimum variance control is introduced into the multivariable system performance assessment,and the weight matrix is designed according to the time-varying control ***,the multivariable MMGMV controller is designed combining with the idea of multi-model weights mixing for all multi-time-varying ***,the output variance of each controlled variable is obtained using MMGMV *** average variance of controlled variable in the MMGMV controller acts as the criterion of performance assessment,and combining with the output variance of actual controller for the controller performance *** with the minimum variance benchmark,the developed method is more reasonable and practical for the control performance assessment of multivariable *** developed approach is demonstrated by a numerical simulation and a heavy oil fractionation of process control system.

关键词： Multivariable Multi-time-variant-disturbance-mixing Generalized minimum variance Time-varying weight matrix Mixing weight

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Locust behaved particle swarm optimization technique 3

Locust behaved particle swarm optimization technique

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Zhong, Wei-Min Xie, Xue-Qin Liang, Yi Luo, Na Zhang, Juan Qian, Feng East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

The collective behavior of certain animals and insects has the characteristic of self-organization. The simple interactions among individuals can produce complex adaptive patterns at the level of the group. Recently, new scientific investigation pointed out that desert locusts show extreme phenotypic plasticity in transforming between the lonely phase and the swarming gregarious phase depending on the population density, which is controlled by a serotonin called 5-hydroxytryptamine. In this paper, based on the mechanism of the locusts' collective behavior, a new particle swarm optimization technique called LBPSO is studied. The number of swarms is self-adaptively adjusted by the acquired outstanding particles coming from behind the previous global best solution. The swarm sizes are related to the corresponding serotonin 5-hydroxytryptamine which is determined by the optimization parameters such as global best, iteration number etc. And each swarm adopts one of three rules below according to its density, generalized social evolution strategy, generalized cognition evolution strategy and the independent moving strategy. A comparative study of LBPSO, SPSO, Improved SPSO and the original PSO on their ability of tracking optima is carried out. And the results under four static benchmark functions and a dynamic function generator MPB show that LBPSO outperforms the other three functions in both static and dynamic landscapes due to the introduced locusts' collective behavior.

关键词： Iterative methods

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Localization with a mobile anchor using ABC-GA hybrid algorithm in wireless sensor networks

Localization with a mobile anchor using ABC-GA hybrid algori...

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

作者： Li, Sijin 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

Nodes localization plays an important role in applications of wireless sensor networks. In this paper, a localization scheme with a mobile anchor using a hybrid algorithm (ABC-GA) which combines artificial bee colony (ABC) algorithm with the advantages of genetic algorithm (GA) is proposed. The localization scheme determines location of unknown node by the mobile anchor;it has high accuracy without any additional requirements for the hardware of unknown node. The core problem of the scheme is finding the shortest path to traversal all unknown nodes. We use ABC-GA hybrid algorithm to solve this problem. Simulation results show that ABC-GA hybrid algorithm has high convergence rate and strong global search capability and the accuracy of localization scheme is satisfactory.

关键词： Genetic algorithms

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Dynamic multi-objective optimization of chemical processes using modified Bare-bones MOPSO algorithm 3

Dynamic multi-objective optimization of chemical processes u...

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Wang, Shan-Shan Du, Wen-Li Chen, Xu Qian, Feng East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper, a modified Bare-bones MOPSO algorithm is proposed that takes advantage of few parameters of bare-bones algorithm. To avoid premature convergence, Gaussian mutation is introduced;and an adaptive sampling distribution strategy is also used to improve the exploratory capability. Moreover, a circular crowded sorting approach is adopted to improve the uniformity of the population distribution. Finally, by combining the algorithm with control vector parameterization, an approach is proposed to solve the dynamic optimization problems of chemical processes. It is proved that the new algorithm performs better compared with other classic multi-objective optimization algorithms through the results of solving three dynamic optimization problems.

关键词： Bone

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Specific index-related process monitoring using a two-step information extraction method 30

Specific index-related process monitoring using a two-step i...

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30th Chinese control and Decision Conference, CCDC 2018

作者： Zhao, Bo Song, Bing Tan, Shuai Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

ISBN: (纸本)9781538612439

Specific index-related process monitoring covers a wide range of requirements from industrial production. At present, it is still a challenge to divide into the specific index-related information and the specific index-unrelated information more accurately. In this paper, a two-step information extraction method is presented to solve this problem. In the first step, the overall process variables are separated into a strongly related variable set and a weakly related variable set. In the second step, the two sets are further divided into a specific index-related subset and a specific index-unrelated subset, respectively. Two specific index-related subsets form a new subspace related to the specific index. Two specific index-unrelated subsets are combined into a specific index-unrelated subspace. Two T2 statistics are built in the specific index-related subspace and the specific index-unrelated subspace, respectively. Finally, the proposed method is applied for Tennessee Eastman (TE). The results indicate the effectiveness of the proposed method. © 2018 IEEE.

关键词： Indexes Information retrieval Monitoring Principal component analysis Correlation coefficient Correlation Fault detection

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Graph-based semisupervised learning for icing fault detection of wind turbine blade

Graph-based semisupervised learning for icing fault detectio...

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作者： Yi, Huaikuan Jiang, Qinchao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

The detection of blade icing faults in wind farms is an important task in improving the reliability and safety of wind power systems. Detection is primarily achieved through supervised learning, using labeled samples. However, labeling a large volume of data often consumes lots of manpower, which means that semisupervised learning is usually required. This study proposes a graph-based semisupervised learning system to achieve efficient fault detection in wind turbines (WTs). The proposed method detects abnormal samples by optimizing a small amount of labeled and a large amount of unlabeled data. Firstly, feature selection based on mutual information is performed on supervisory control and data acquisition data, so as to eliminate redundant variables. Secondly, a graph is constructed, using the limited labeled data to indicate the connections between samples. Finally, the initial class information is propagated to the entire data set by iteratively updating the input of the graph model. Experimental results based on a selection of benchmark data sets and real WT data demonstrate the feasibility of the proposed method. © 2020 IOP Publishing Ltd.

关键词： Wind turbines

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Event-triggered distributed predictive control for constrained large-scale linear systems 35

Event-triggered distributed predictive control for constrain...

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第35届中国控制会议

作者： SU Xu ZOU Yuanyuan NIU Yugang JIA Tinggang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Automation Division Shanghai Electric Group Co.Ltd

ISBN: (纸本)9781509009107

This paper investigates the problem of event-triggered dual-mode distributed predictive control(DPC) for constrained large-scale linear systems subject to bounded *** on input-to-state stability(ISS) theory,the event-triggering condition involving information of the subsystem itself is derived.A dual-mode predictive control scheme is designed to reduce information exchanges with neighboring *** upper bound of disturbances for ensuring the recursive feasibility and closed-loop stability are ***,a simulation example is given to show that the presented method is able to save computation resources and communication resources while guaranteeing the desired control performance.

关键词： Large-Scale Systems Distributed Predictive control(DPC) Event-Triggered

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Fault diagnosis of CTA hydrogenation process based on KPCA 3

Fault diagnosis of CTA hydrogenation process based on KPCA

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： Li, Bo Li, Zhi Luo, Na Zhong, Weimin East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

As the large amounts of operate data collected from Distributed control System (DCS) often contain outliers and these data are more complexity and nonlinearity. They can't be used directly to model, optimization and fault diagnosis. In fault diagnosis, the existence of outliers can destroy the covariance structure of Kernel Principal Component Analysis (KPCA), which cause the model can't really reflect the actual normal condition. In this paper, KPCA method is adopted to establish the normal statistic monitor model from the historical data which can represent the normal industrial operate condition. First, the outlier detection algorithm is used to eliminate outliers among normal work condition. Then the primary statistic model for fault diagnosis of the Squared Prediction Error (SPE) and T2 are established according to the data exclude outliers. The effectiveness of this fault diagnosis is demonstrated by the operate data of industrial Crude Terephthalic Acid (CTA) hydrogenation process, and simulation results show that this method can identify the industrial failure condition.

关键词： Failure analysis

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