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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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On-Line Batch Process Monitoring Using Multiway Kernel Partial Least Squares

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Journal of Donghua University(English Edition) 2011年第6期28卷 585-590页

作者：胡益马贺贺侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

An approach for batch processes monitoring and fault detection based on multiway kernel partial least squares(MKPLS) was *** is known that conventional batch process monitoring methods,such as multiway partial least squares(MPLS),are not suitable due to their intrinsic linearity when the variations are *** address this issue,kernel partial least squares(KPLS) was used to capture the nonlinear relationship between the latent structures and predictive *** addition,KPLS requires only linear algebra and does not involve any nonlinear *** this paper,the application of KPLS was extended to on-line monitoring of batch *** proposed batch monitoring method was applied to a simulation benchmark of fed-batch penicillin fermentation *** the results demonstrate the superior monitoring performance of MKPLS in comparison to MPLS monitoring.

关键词： process monitoring fault detection kernel partial least squares(KPLS) nonlinear process multiway kernel partial least squares(MKPLS)

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Component Content soft-sensor of SVM based on Ions color characteristics

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Telkomnika 2012年第6期10卷 1445-1452页

作者： Rongxiu, Lu Hui, Yang Kunpeng, Zhang School of Electrical Mechanical and Electrical Engineering Nanchang University Nanchang Jiangxi 330031 China School of Electrical and Electronic Engineering East China Jiaotong University Nanchang Jiangxi 330013 China Key Laboratory of Advanced Control and Optimization of Jiangxi Province Nanchang Jiangxi 330013 China

In consideration of different characteristic colors of Ions in the P507-HCL Pr/Nd extraction separation system, ions color image feature H, S, I that closely related to the element component contents are extracted by using image processing method. Principal Component Analysis algorithm is employed to determine statistics mean of H, S, I which has the stronger correlation with element component content and the auxiliary variables are obtained. With the algorithm of support vector machine, a component contents soft-sensor model in Pr/Nd extraction process is established. Finally, simulations and tests verify the rationality and feasibility of the proposed method. The research results provide theoretical foundation for the online measurement of the component content in Pr/Nd countercurrent extraction separation process.

关键词： Extraction

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Classification of four-class motor imagery EEG based on CSP-HMM

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 197-201页

作者： Wang, Dong-Yang Jin, Jing Wang, Xing-Yu Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

In this paper, a new classification method based on common spatial pattern (CSP) and hidden markov model(HMM)is presented to classify the EEG of four-class motor imagery. 4 s data of motor imagery is selected and four 2 s sub-data sets are obtained by sliding time window with 0.5 s step size. CSP is used to extract features from the four sub-data sets respectively. Features from each class are used to train one HMM. Four different HMMs are obtained corresponding with the four classes. Test data are measured by the four HMMs and classified based on the maximum likelihood obtained from the four HMMs. The results show that HMM yields better performance than Bayesian linear discriminant analysis.

关键词： Brain computer interface

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Attribute reduction based on ant colony algorithm for optimization of minimal reductions

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 48-52页

作者： Yin, She-Jie Zhang, Ling-Bo Gu, Xing-Sheng Xu, Zhen-Hao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

Attribute reduction is an important topic of the rough set theory and it's a NP-hard problem to find a minimal reduction. Due to the advantage of ant colony algorithm in solving combinatorial optimization problems, this paper treats attribute reduction as a combinatorial optimization problem, and combines the rough set theory with ant colony algorithm to search the minimal reduction. In accordance with the problems in obtaining many minimal reduction sets of the same length, the paper takes the dependence degree of decision attributes on the non-core attributes to measure the solutions and selects the reduction set which has the maximum dependence degree, so as to find the optimal solution. Experimental results verify the validity of the presented algorithm.

关键词： Rough set theory

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Immune response-based algorithm for optimization of dynamic environments

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Journal of Central South University 2011年第5期18卷 1563-1571页

作者：史旭华钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology College of Information Science and Engineering Ningbo University

A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response *** dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was *** the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was *** addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching *** traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic *** reported algorithms were compared with AIDE by using Moving Peaks *** experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the ***,AIDE is useful for the optimization of dynamic environments.

关键词： dynamic optimization artificial immune algorithms immune response multi-scale variation

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Analysis and discussion of group mobility management in ubiquitous network

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 299-305页

作者： Cao, Jian-Fu Ling, Zhi-Hao Yuan, Yi-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

In order to research the group mobility management technology, the research progress of group mobility management in ubiquitous network is summarized. Based on the new features of the ubiquitous network, the structures, performances and application fields of group mobility model are discussed, and some key technologies such as context awareness, service decision-making, cooperative transmission and radio resource management are also introduced. Aiming at the challenges in this filed, some solutions and valuable research directions are proposed.

关键词： Decision making

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A comparison of three electrode channels selection methods applied to SSVEP BCI

A comparison of three electrode channels selection methods a...

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Meng, Lijing Jin, Jing Wang, Xingyu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai China

ISBN: (纸本)9781424493524

There has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain-computer interface systems (BCIs). The electrode channels usually used in SSVEP classification are O1, O2 and Oz. However, optimal results of SSVEP recognition could not be obtained from the same electrode setting (O1, O2 and Oz), which was caused by subject variation. In this paper, three methods (Sequential floating forward selection (SFFS), discrete particle swarm optimization (DPSO) and F-score) were employed to select the optimal electrode channels. The electrode channels obtained by SFFS, DPSO and F-score were compared with traditional electrode channels (i.e., O1, O2 and Oz), which are usually used in SSVEP BCI. The results show that SFFS and DPSO can obtain higher classification accuracy than traditional approach. The results also show that SFFS is superior to DPSO in terms of calculating time, and F-score is not good compared to other two methods. Channel selection can not only reduce features for data analysis but also reduce the time for channel installation. © 2011 IEEE.

关键词： Brain computer interface

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A hybrid method for identifying T-S fuzzy models

A hybrid method for identifying T-S fuzzy models

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Wang, Honggang Zhao, Liang Du, Wenli 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)9781612841816

This paper presents a hybrid approach to extract compact Takagi-Sugeno fuzzy models from numeric data, using subtractive clustering (SC), particle swarm optimization (PSO) and least square method. The feature of this method lies in the following: (1) the input space is partitioned and initial fuzzy rule bases are extracted by SC;(2) the optimal parameters of the membership functions are evolved by PSO, based on the initial fuzzy rule bases;(3) the consequent parameters of the rule base are analytically derived by the Moore-Penrose pseudo inverse, instead of being iteratively tuned. Simulation results in Mackey-Glass chaotic time series prediction and nonlinear plant modeling problems show that the proposed method is effective and robust in finding compact and accurate T-S fuzzy models. © 2011 IEEE.

关键词： Membership functions

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A data-driven soft sensor modeling for furnace temperature of opposed multi-burner gasifier

A data-driven soft sensor modeling for furnace temperature o...

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2011 7th International Conference on Natural Computation, ICNC 2011

作者： Li, Jie Zhong, Weimin Cheng, Hui Kong, Xiangdong 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)9781424499533

The Opposed Multi-Burner (OMB) Coal-Water Slurry (CWS) gasification is a new large-scale coal gasification technology with higher product yield, lower oxygen and coal consumption than that of Texaco CWS gasification technology. However, current furnace temperature measurements of OMB and other gaisifiers are unstable and even short-life due to the extreme internal environment: high temperature, strong corrosion, etc. Therefore a new data-driven soft sensor modeling technique for furnace temperature of OMB gasifier is proposed and the selection of secondary variables and model structure of BP neural network is studied in this paper. Results indicate that, the furnace temperature predictive model integrating Principal Component Analysis (PCA) and BP neural network has a promising performance with good predictive precision. © 2011 IEEE.

关键词： Coal

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