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作者： Ji, Jun Wang, Hai-Qing Chen, Kun Yang, Dian-Cai State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou 310027 China MESNAC National Tire Process and Control Engineering Research Center Qingdao China

Fed-batch processes are inherently difficult to model owing to non-steady-state operation, small-sample condition, instinct time-variation and batch-to-batch variation caused by drifting. Furthermore, when the process switches to different operation phrases, global learning modeling methods would suffer poor performance due to the negative impact of overdue training samples. In this paper, a k nearest neighbor relevance vector machine (kNN-RVM) based lazy learning method is proposed to model the fed-batch processes to soft-sense the corresponding production indices. A recursive algorithm is developed to effectively obtain the kernel matrices used by previous kNN step and following modeling process. Simulative soft-sensors of penicillin production process and rubber mixing process are implemented to valid the proposed method. Comparative results indict that proposed method has better precision and much lower computational complexity than relevance vector machine (RVM) on soft-sensing modeling of fed-batch processes. © 2011 Zhejiang University.

关键词： Nearest neighbor search

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Structure restricted (PID) controller performance assessment for multi-stage batch processes with tracking and regulatory requirements

Structure restricted (PID) controller performance assessment...

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作者： Fu, Ruowei Xie, Lei Song, Zhihuan Institute of Industrial Process Control Department of Control Science and Technology Zhejiang University Hangzhou 310027 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China

A new control performance assessment method based on a structured residual for multi-stage batch processes is presented. After separating the process into different stages according to reference signal dynamics, based on specific tracking and regulatory requirements of different stage, a structured residual focusing on deterministic part of output error with different weights on each stage is minimized to form the performance benchmark. In this way, it explores the equilibrium control effect in tracking and regulatory stages of batch processes in the whole batch sense. The best control performance with respect to stage balance and the overall optimal controller settings are searched using Newton's method. The application to an exothermic chemical batch reactor shows its effectiveness and feasibility. © 2011 Zhejiang University.

关键词： Batch reactors

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A less conservative H∞ fault-tolerant control for NCS based on T-S fuzzy model

A less conservative H∞ fault-tolerant control for NCS based...

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3rd International Conference on Measuring technology and Mechatronics Automation, ICMTMA 2011

作者： Wang, Jun Li, Wei Li, Zhanming College of Electrical and Information Engineering Lanzhou University of Technology Key Laboratory of Advanced Control for Industrial Process in Gansu Province LanZhou Gansu 730050 China

ISBN: (纸本)9780769542966

For a class of nonlinear networked control system (NCS) with network-induced delay and packed dropout, which is influenced by external disturbance with limited energy in transmission, a T-S fuzzy model is employed to represent the nonlinear controlled plant. By using appreciate Lyapunov-Krasovskii function, a H∞ integrality sufficient condition against actuator failures is derived based on delay-dependent approach, and the H∞ fault-tolerant controller gain can be obtained via solving several linear matrix inequalities(LMIs). Because of the lower bound of the time-delay and free weighting matrixes are introduced, and the model transformation has not been used. Then a less conservative result is obtained. Finally, an example is used to illustrate the effectiveness and feasibility of proposed approach.

关键词： Networked control systems

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Robust fault-tolerant control for uncertain NCS based on dynamic output feedback

Robust fault-tolerant control for uncertain NCS based on dyn...

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International Conference on Measuring technology and Mechatronics Automation

作者： Li, Wei Cao, Huichao Wang, Jun Key Laboratory of Advanced Control for Industrial Process in Gansu Province College of Electrical and Information Engineering Lanzhou University of Technology LanZhou Gansu 730050 China

ISBN: (纸本)9780769542966

This paper investigates the problem of robust integrality for networked control system with norm-bounded parameter uncertainties. Both network-induced delay and data packet dropout are taken into consideration, and data packet dropout is regard as a kind of special delay. A new type of Lyapunov-Krasovakii functional is proposed which contains some triple-integral terms. Based on dynamic output feedback control strategy, a delay-dependent robust integrality sufficient condition against actuator failures is derived in terms of integral inequality technique. Because the model tranformation is not used and the lower bound of delay is introduced, meanwhile, we don't ignore some useful items when estimating the upper bound of derivative of Lyapunov-Krasovskii function, the results possess less conservativeness. Moreover, the design approach of the controller are given via solving linear matrix inequalities. Finally, an example is used to illustrate the effectiveness and the feasibility of proposed approach. © 2011 IEEE.

关键词： Networked control systems

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Growth of micro/nano-structured metal oxides on carbon fiber and construction of flexible devices

Growth of micro/nano-structured metal oxides on carbon fiber...

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2011 International Conference on advanced Fibers and Polymer Materials, ICAFPM 2011

作者： Ma, Xingfa Liu, Sha Gu, Sihui Zheng, Jing He, Xiaochun Gao, Mingjun Zhang, Xintao Li, Guang School of Environmental and Material Engineering Center of Advanced Functional Materials Yantai University Yantai 264005 China State Key Laboratory of Silicon Materials Zhejiang University Hangzhou 310027 China National Laboratory of Industrial Control Technology Institute of Advanced Process Control Zhejiang University Hangzhou 310027 China

ISBN: (纸本)9787122120199

Carbon fibers are attractive substrates to be used for designing flexible and weavable devices. In order to obtain some flexible chemical sensors or other nanodevices, surface treatment of carbon fiber was carried out with oxidation approach. Studies on preparation of some typical metal oxide or other inorganic functional film (such as, ZnO, NiO, CdS, et al) with different morphologies under hydrothermal reaction condition were examined. A series of characterizations were employed by scanning electron microscope (SEM), X-ray diffraction (XRD), photoluminescence spectra (PL), et al. Results indicated that the ZnO film with porosity was uniformly formed on the surface of carbon fibers, and the uniformities of other films will be improved further by adjusting synthesis conditions.

关键词： Carbon fibers

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Short-term load combined forecasting method based on BPNN and LS-SVM

Short-term load combined forecasting method based on BPNN an...

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2011 IEEE Power Engineering and Automation Conference, PEAM 2011

作者： Zhang, Ming-Guang Li, Lin-Rong School of Electrical Engineering Lanzhou University of Technology Gansu 730050 China Key Laboratory of Gansu Advanced Control for Industrial Process Gansu Lanzhou 730050 China

ISBN: (纸本)9781424496884

Load forecasting, especially short-term load forecasting is of great significance for the planning, scheduling, marketing of power system. In order to predict the daily load as accurate as possible,a combined prediction method based on Least Squares Support Vector Machine (LS-SVM) and BP Neural Network (BPNN) is proposed in this paper. The historical load of relational better six-day ahead and the day type are selected as input,and got 1-dimensional output variable. Two sets of different prediction results are obtained from LS-SVM method and BPNN method, which is combined by using the method of minimum variance to research the final prediction results. The load prediction results of northwest grid show that the combined forecasting method has better prediction accuracy than LS-SVM and BPNN method. Therefore, this method is efficient and practical for a short-term load forecasting of electric power system. © 2011 IEEE.

关键词： Forecasting

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Adaptive Critic-Based Tracking control of Non-Affine Nonlinear Discrete-time Systems with Unknown Dynamics

Adaptive Critic-Based Tracking Control of Non-Affine Nonline...

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2011 China control and Decision Conference(2011中国控制与决策会议 CCDC)

作者： Qinmin Yang Youxian Sun State Key Laboratory of Industrial Control Technology Institute ofIndustrial Process Control Zheji State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhej

ISBN: (数字)9781424487387

ISBN: (纸本)9781424487370

In this paper, the tracking control of a class general non-affine discrete-time unknown systems represented by the nonlinear autoregressive moving average with eXogenous input (NARMAX) representation is discussed. An equivalent affine-like representation in terms of the tracking error dynamics is first obtained from the original nonaffine nonlinear discrete-time system so that a robust adaptive critic-based neural network controller can be developed. The control scheme consists of an action NN for compensating the unknown system dynamics, and a critic NN to approximate certain strategic utility function and to tune the action NN weights. The NN weights are tuned an online manner without the need of the knowledge of the system dynamics. By using the standard Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error is shown. Simulation results are given substantiate the theoretical conclusions.

关键词： Non-affine nonlinear systems adaptive critic neural networks discrete-time

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Bayesian statistical monitoring of complex semiconductor manufacturing batch processes

Bayesian statistical monitoring of complex semiconductor man...

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作者： Ge, Zhiqiang Zheng, Junhua Song, Zhihuan Dai, Huaping State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou 310027 Zhejiang China Zhejiang Titan Design and Engineering Co. LTD. Hangzhou Zhejiang China

ISBN: (纸本)9783902661937

Most current batch process monitoring methods have been implemented under a single operation mode, thus the batch uncertainty is assumed to be caused by batch-to-batch variations. However, due to the change of market requirements, the batch operation mode should also be changed frequently, especially in the semiconductor manufacturing process. This paper proposes an efficient method for monitoring those batch processes. First, the data is partitioned into multiple clusters, which correspond to different operation modes. Second, a sub-statistical model is built for each operation mode. Then the Bayesian inference strategy is introduced for result combination in different operation modes. The monitoring performance of the proposed method is evaluated by a real semiconductor process application case study. © 2011 IFAC.

关键词： Batch data processing

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Fault detection and identification: serial form versus simultaneous form

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IFAC Proceedings Volumes 2011年第1期44卷 2827-2832页

作者： Zhibo Zhu Zhiqiang Ge Zhihuan Song Li Zhao State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou 310027 Zhejiang China

Abstract Pattern recognition techniques have been widely applied for fault diagnosis. In this paper, two different forms, named serial form and simultaneous form, of pattern recognition based fault detection and identification systems are discussed. The optimal form is selected by a performance assessment rule which is based on the overall fault diagnosis system loss. Beside of considering the fault detection and isolation performance of the classifiers, the misclassification costs in both of the fault detection and isolation stages have also been considered for selecting the optimal form. In order to compare the performance of these two forms, two novel fault detection and isolation approaches integrating kernel principal component analysis (KPCA) and support vector data description (SVDD) are proposed subsequently. A simulation case study of Tennessee Eastman (TE) process is presented to evaluate the proposed fault detection and isolation methods.

关键词： fault detection fault isolation pattern recognition

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Improved two-dimensional dynamic batch process monitoring with support vector data description

Improved two-dimensional dynamic batch process monitoring wi...

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作者： Ge, Zhiqiang Gao, Furong Song, Zhihuan State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou 310027 Zhejiang China Department of Chemical and Biomolecular Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9783902661937

For dynamic batch process monitoring, a two-dimensional dynamic modeling framework has recently been formulated, which is based on a two-dimensional autoregressive model and the principal component analysis (PCA) method. Different from traditional dynamic batch process monitoring, the two-dimensional method can monitor both within batch and batch-to-batch dynamic information of the process data. However, this PCA-related method has two main restrictions, which may render poor monitoring performance in practice. First, it is under the assumption that the distribution of the process data is Gaussian. Second, the correlations between different process variables are assumed to be linear with each other. Unfortunately, both of these two assumptions are difficult to satisfy in batch processes. In this paper, support vector data description (SVDD) is incorporated into the two-dimensional modeling framework, which has no Gaussian limitation of the data, and can also model the nonlinear relationship between process variables. For dynamic batch process monitoring, a distance based statistic is proposed. Based on results of a simulation case study, the monitoring performance has been improved. © 2011 IFAC.

关键词： Principal component analysis

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