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Fault Detection Filter Design for Linear Polytopic Uncertain Continuous-time Systems

Acta Automatica Sinica 2010年第5期36卷 742-750页

作者： Heng WANG He-Hua JU Guang-Hong YANG College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100124 P. R. China Key Laboratory of Integrated Automation for the Process Industry Ministry of Education Shenyang 110004 P. R. China College of Information Science and Engineering Northeastern University Shenyang 110004 P. R. China

The paper studies the problem of fault detection filter design for uncertain linear continuous-time systems. A design procedure dealing with parameter uncertainties is proposed for residual generation, the sensitivity to fault and the robustness against disturbances are both enhanced on residual outputs through satisfying some performance indexes. By the aid of the generalized Kalman-Yakubovich-Popov (GKYP) lemma, the fault sensitivity performance index can be dealt with in the given frequency range directly, which avoids approximations associated with frequency weights of the existing techniques. An iterative algorithm based on linear matrix inequality (LMI) is given to obtain the solutions. A numerical example is given to illustrate the effectiveness of the proposed methods.

关键词： Fault detection polytopic uncertainty Kalman-Yakubovich-Popov (GKYP) lemma linear matrix inequality (LMI)

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Modelling of mill load for wet ball mill via GA and SVM based on spectral feature

Modelling of mill load for wet ball mill via GA and SVM base...

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

作者： Lijie Zhao Jian Tang Wen Yu Heng Yue Tianyou Chai College of Information Engineering Shenyang University of Chemical Technology Shenyang China Key Laboratory of Integrated Automation of Process Industry Northeastern University Shen yang Liaoning China Departamento de Control Automatico CINVESTAV-IPN Mèxico Mexico

The load of wet ball mill is a key parameter for grinding process, which affects the productivity, quality and energy consumption. A new soft sensor approach based on the mill shell vibration signal is proposed in this paper. As the frequency domain signal contains more evidently information than time domain, the power spectral density (PSD) of the vibration signal was obtained via fast Fourier transform (FFT). And then the mass and the central frequency of the small peaks of the spectrum are extracted as the spectral features. At last the support vector machines (SVM) is used to build the soft model. The parameters of SVM, the input variables including the mass and the central frequency of the peaks are selected by Genetic algorithm (GA). Experimental results show that proposed soft sensor model has higher accuracy and better predictive performance than the other normal approaches.

关键词： Support vector machines Genetic algorithms Gallium Irrigation

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Dynamic Prediction Model for Mixed Concentrate Grade of Mineral processing Plant

Dynamic Prediction Model for Mixed Concentrate Grade of Mine...

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2010 49th IEEE Conference on Decision and control

作者： Jinliang Ding Tianyou Chai Hong Wang Key Laboratory of Integrated Automation of Process Industry(Northeastern University) Ministry of Education Shenyang 110004 P.R. China Control Systems Center School of Electrical and Electronic Engineering The University of Manchester Manchester M13 9PL UK

ISBN: (纸本)9781424477456

A non-linear modelling approach of dynamic prediction model for mixed concentrate grade consisting of a linear part and a nonlinear part is developed. The nonlinear part is implemented using the least squares support vector machine (LS-SVM), where the problem of selecting model parameters is transformed into the probability distribution function (PDF) control of the modelling error. Both the PDF control based and minimum entropy based model parameter selection approaches are proposed. The experiment results show the effectiveness of the proposed approaches.

关键词： concentrate grade Prediction models mineral processing plants model parameters

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Behavior of a Logistic Map Driven by White Noise

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中国物理快报（英文版） 2009年第6期26卷 63-66页

作者： YANG Zheng-Ling GAO Yang GAO Yong-Tao ZHANG Jun School of Electrical Engineering and Automation Tianjin UniversityTianjin 300072 Tianjin Key Laboratory of Process Measurement and Control Tianjin300072

In the real world,every nonlinear system is inevitably affected by *** an example,a logistic map driven by white noise is *** previous studies which focused on the behavior under local parameters to find analytical results,we investigate the whole driven logistic *** a white noise driven logistic map,its nondivergent interval decreases with increasing white *** white noise does not change the equilibrium point and two-cycle intervals in statistics,if the driven logistic map is kept *** particular,chaos can be excited by white noise only after the four-cycle bifurcation *** latest result is a necessary condition which has not been given in the literature[*** 18 (2008) 509],and it can be deduced from Sharkovsky's *** simulations prove these analytical results.

关键词： No English Keywords

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Feature selection and classification of breast cancer on dynamic Magnetic Resonance Imaging by using artificial neural networks

Feature selection and classification of breast cancer on dyn...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Farzaneh Keivanfard Mohammad Teshnehlab Mahdi Aliyari Shoorehdeli Ke Nie Min-Ying Su Electrical and Computer Engineering Department Khaje Nasir Toosi University of Technology Tehran Iran Electrical and Computer Engineering Department Advanced Process Automation and Control (APAC) Khaje Nasir Toosi University of Technology Tehran Iran Center for Functional Onco-Imaging and Department of Radiological Sciences University of California Irvine CA USA

In this paper, a new feature selection and classification methods based on artificial neural network are applied to classify breast cancer on dynamic Magnetic Resonance Imaging (MRI). The database including benign and malignant lesions is specified to select the features and classify with proposed methods. It is collected from 2004 to 2006. A forward selection method is applied to find the best features for classification. Moreover, artificial neural networks such as Multilayer Preceptron (MLP) neural network, Probabilistic Neural Network (PNN) and Generalized Regression Neural Network (GRNN) are applied to classify breast cancer into two groups; benign and malignant lesions. Training and recalling neural networks are obtained with considering four-fold cross validation.

关键词： Fires Entropy Correlation Artificial neural networks Lesions Jacobian matrices Kinetic theory

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Tension Soft Sensor of Continuous Annealing Lines Using Cascade Frequency Domain Observer with Combined PCA and Neural Networks Error Compensation

Tension Soft Sensor of Continuous Annealing Lines Using Casc...

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2010 49th IEEE Conference on Decision and control

作者： Qiang Liu Tianyou Chai Hong Wang S. Joe Qin Key Laboratory of Integrated Automation of Process Industry (Northeastern University) Ministry of Education and Research Center of Automation Northeastern University Shenyang China Control Systems Centre the University of Manchester Manchester M60 1QD the United Kingdom Mork Family Department of Chemical Engineering and Materials Science the Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles CA 90089-1211 USA

ISBN: (纸本)9781424477456

In continuous annealing processes, strip tension is an important factor which indicates whether the annealing line works steadily. The strip tension detection in the continuous annealing process, therefore, is essential for the reliable and stable operation of the units, and will help to improve the quality of strip products. However, in real annealing processes, only a limited number of strip tensions can be measured. Since installing tension sensors everywhere will be unrealistic and expensive, in this paper a cascade reduced-order observer method with principal component analysis (PCA) and neural networks (NN) compensation is proposed to estimate the unknown tensions between each two neighboring rolls so as to monitor the tension profile for the whole line. When the main observer model is established, the influences of strip inertia and roll eccentricity on tensions are taken into account for better estimation. Moreover, when the error compensation is designed, PCA scores are used as the inputs to the NN. The application results show the effectiveness of the proposed method, with the estimated tensions used for the analysis of the strip-breaks fault.

关键词： Error compensation Continuous annealing annealing tension strip tension stability operations Neural network cascades

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Identification of nonlinear static processes with local polynomial regression and subset selection

Identification of nonlinear static processes with local poly...

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15th IFAC Symposium on System Identification, SYSID 2009

作者： Sequenz, Heiko Schreiber, Alexander Isermann, Rolf Institute of Automatic Control Laboratory of Control Engineering and Process Automation Technical University Darmstadt Germany

ISBN: (纸本)9783902661470

The presented method for nonlinear system identification is based on the LOLIMOT algorithm introduced by Nelles and Isermann [1996]. The LOLIMOT algorithm divides the input space by a tree-construction algorithm and interpolates the local linear models by local membership functions. Instead of assuming local linear models, the presented algorithm utilizes general local nonlinear functions, which make the algorithm more flexible. These are approximated by a multidimensional Taylor series. Since the amount of regressors grows fast with the number of inputs and the expansion order, a subset selection procedure is introduced. It reveals significant regressors and gives information about the local functional behavior. The local subset selection is implemented as a stepwise regression with replacement of regressors. Mallows' Cp-statistic is used for the subset selection algorithm and is also implemented for final model selection. The benefit of the extended algorithm lies in the higher flexibility in the local models, which results in less partitions of the input space by a similar approximation quality. © 2009 IFAC.

关键词： Membership functions

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Flow Rate Measurement of Oil/Gas/Water Three‐Phase Flow with V‐Cone Flow Meter

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AIP Conference Proceedings 2010年第1期1207卷

作者： F. S. Zhang F. Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

Mass flow rate is an important parameter of oil/gas/water three‐phase flow, most multi‐phase flow meters are based on the measurement of total mass flow rate and phase fraction. As the Reynolds number of three‐phase flow grows to a certain number, the oil and water phase are considered as a homogenous mixture with a mixed density. In this case, oil/gas/water three‐phase flow could be measured as gas/liquid two‐phase flow. A V‐cone flow meter with beta ratio of 0.65 is used to make the mass flow rate measurement, the calibration experiment is carried out with oil/water flow, the effect of oil proportion and the mixture Reynolds number on the discharge coefficient of V‐cone flow meter is discussed. Comparison of four typical differential pressure correlations is put forward under experiment condition. Lin correlation best behaved in the experiment and error analysis is done based on it. The experiment result shows the mass flow rate of oil/gas/water flow could be measured by V‐cone flow meter efficiently and the experiment error is acceptable.

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Absolute stability of Lur'e singularly perturbed systems with multiple nonlinearities

Absolute stability of Lur'e singularly perturbed systems wit...

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American control Conference

作者： Chunyu Yang Qingling Zhang Jyh-Horng Chou Yingwei Zhang Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Institute of Systems Science Northeastern University Shenyang 110004 P.R. China Institute of System Information and Control Engineering National Kaohsiung First University of Science and Technology I University Road Yuanchau Kaohsiung 824 Taiwan

ISBN: (纸本)9781424474264

This paper investigates the absolute stability problem for Lur'e singularly perturbed systems with multiple nonlinearities. The objective is to determine if the system is absolutely stable for any epsilon E (0, (epsilon)_(0)], where epsilon denotes the perturbation parameter and (epsilon)_(0) is a pre-defined positive scalar. Firstly, an epsilon-dependent Lyapunov function of Lur'e-postnikov form is constructed. Then, a stability criterion expressed in terms of epsilon-independent linear matrix inequalities (LMIs) is derived. Finally, an example is given to show the feasibility and effectiveness of the obtained method.

关键词： Robust stability Stability criteria control systems Lyapunov method Power system stability Power system modeling Educational institutions Nonlinear control systems control nonlinearities USA Councils

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Improved Multidisciplinary Multiobjective Collaborative Optimization Technique Based on NSGA-II Algorithm 1

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IFAC Proceedings Volumes 2010年第25期43卷 139-144页

作者： H. Li Y. Jing S. Zhang V. Ojleska T. Kolemisevska G.M. Dimirovski Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Northeastern University School of Information Science & Engineering Shenyang 110004 P.R. China SS Cyril and Methodius University School FEIT Institute of ASE Karpos II BB MK-1000 Skopje R. Macedonia Dogus University Computer Eng. and Control Eng. Departments TR-34722 Istanbul Turkey

The multiobjective collaborative optimization (MCO) has been widely adopted in concurrent engineering design as a good multiobjective optimization approach provided the problem of optimization results converging often to a local extremum has been taken care of. It has been demonstrated to yield useful solutions to a wide range of optimization problems under concurrent condition both technical and non-technical ones. A solution strategy for MCO that overcomes this drawback is proposed here on the grounds of genetic NSGA-II algorithm. It is an adaptive heuristic search technique that controls the distances between the individual and system's feasible region during genetic evolution. In the evolving NSGA-II based non-dominated sorting, the individual threshold of infeasibility degree is reduced gradually via genetic evolution and the individual's feasibility capacity is determined by its infeasibility degree and the threshold. It has been applied to a benchmark example of speed reducer design, and the obtained results demonstrate the proposed technique is comparably more efficient and may offer substantial advantages over the gradient-based optimization methods. Copyright © 2010 IFAC

关键词： Collaborative optimization dynamic threshold genetic algorithms multidisciplinary optimization multiobjective optimization

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