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International Conference on Developments in esystems engineering (DESE)

作者： Sonia Alimi Mohamed Chtourou Research unit on Intelligent Control design and Optimization of complex Systems (ICOS) Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia

This paper presents the stability analysis of parameter identification. The Takagi Sugeno fuzzy model is employed to represent the discrete time nonlinear dynamical systems. Once the structure of the fuzzy model is fixed, the parameters can be optimized. The parameter identification is accomplished by applying the gradient method where the iteration rates are specific to each parameter. The stability of this algorithm is discussed by using two approaches which guarantee that the system is stable if the iteration rates satisfy sufficient conditions. The first approach deals with the consequence parameters and the second one deals with the premise parameters.

关键词： Stability analysis Fuzzy systems Parameter estimation Design engineering Lyapunov method Linear matrix inequalities Intelligent control Design optimization Sufficient conditions Nonlinear systems

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Conservative power theory discussion and evaluation by means of virtual instrumentation

Conservative power theory discussion and evaluation by means...

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Brazilian Power Electronics Conference, COBEP

作者： Helmo K. M. Paredes Fernando P. Marafão Danilo I. Brandão Ivando S. Diniz School of Electrical and Computer Engineering Department of Electrical Energy Systems State University of Campinas-UNICAMP Sao Paulo Brazil Control and Automation Engineering Group of Automation and Integrating Systems São Paulo State University Sao Paulo Brazil

Considering different single and multiphase circuits feeding linear and non-linear loads, this paper presents theoretical discussions and experimental evaluation of the recent Conservative Power Theory (CPT), by means of Virtual Instrumentation concepts. The main goal is to analyze the results of such power theory definitions under nonsinusoidal and unbalanced conditions, pointing out its major advantages, possible drawbacks or relevant aspects for discussion.

关键词： Instruments Circuits Voltage Power engineering and energy Reactive power automation Power electronics Power engineering computing Automatic control Nonlinear control systems

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Meshless local Petrov-Galerkin method for bioluminescent photon propagation in the biological tissue

Meshless local Petrov-Galerkin method for bioluminescent pho...

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Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Qin, Chenghu Tian, Jie Yang, Xin Liu, Kai Feng, Jinchao Xua, Min Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences P. O. Box 2728 Beijing 100190 China Life Science Center Xidian University Xi'an Shaanxi 710071 China The College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100124 China

ISBN: (纸本)9780819475138

As a promising optical molecular imaging modality, bioluminescence tomography (BLT) has attracted remarkable attention for its excellent performance and high cost-effectiveness, which can be employed to speciffically and directly reveal physiological and pathological activities in vivo at molecular and cellular levels. The goal of BLT is to reconstruct the internal bioluminescent light source with surface measurements. Therefore, the calculation of surface light exitance plays an important role in the inverse source reconstruction, whereas photon propagation is complicated because of strongly scattering property of the biological tissue. In this contribution, a novel meshless local Petrov-Galerkin (MLPG) method based on diffusion approximation model is developed to avoid the complex and time-consuming mesh division in the conventional finite element method (FEM), and MLPG requires only a series of discretized nodes without consideration of element information and node connectivity. Compared with other meshless methods based on global weak-form, background cells used for Gauss quadrature are also omitted in the proposed method. In addition, the tissue optical parameters are incorporated as a priori knowledge in this algorithm. Finally, the performance of this method is valuated using two- and three-dimensional numerical simulation experiments. The results demonstrate the effectiveness and feasibility of the presented algorithm to predict boundary bioluminescent light power distribution. © 2009 SPIE.

关键词： Finite element method

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Higher-order model-free adaptive control for permanent magnet linear motor

Higher-order model-free adaptive control for permanent magne...

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Chinese control and Decision Conference, CCDC

作者： Rong-hu Chi Zhong-sheng Hou Institute of Autonomous Navigation and Intelligent Control School of Automation and Electrical Engineering Qingdao University of Science and Technology Qingdao China Advanced Control Systems Lab School of Electronics & Information Engineering Beijing Jiaotong University 100044 China

A higher-order model-free adaptive control is presented for improving the permanent magnet linear motor position and velocity tracking performance. The controller is comprised of the adaptive control law and the PPD updating law. The control law gain is not linear but expressed by a nonlinear function with the PPD parameter tuned on-line by the updating law. The control design is model-free and just depends on the I/O data of the system, without requiring any other priori. By introducing higher-order learning law, this method can incorporate more control information obtained in previous sampling time instants, with a result of improving the convergence performance greatly. Simulation results illustrate the validity of the presented method.

关键词： Adaptive control Permanent magnet motors Partial response channels Navigation Intelligent control automation control system synthesis Automatic control Gain control design

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Decentralized Fault Detection System Design For Large-scale Interconnected System

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IFAC Proceedings Volumes 2009年第8期42卷 816-821页

作者： W. Li W.H. Gui Y.F. Xie S.X. Ding Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg 47057 Germany (Tel: +***) School of Information Science and Engineering Central South University Changsha 410083 P.R. China

In this paper, a decentralized fault detection (FD) system design approach is proposed for discrete-time large-scale interconnected systems. Such an FD system consists of two parts for each subsystem: a residual generator and a residual evaluator. The residual generator producing weighted output estimation errors is designed to match a proper reference residual model, such that it is robust against system disturbances and sensitive to system faults. The solution to a (sub)-optimal residual generator is given by solving a convex optimization problem with the help of linear matrix inequalities (LMIs). Then norm based evaluation functions are selected for each subsystem and the corresponding thresholds are presented for the residual evaluator design. The computation of thresholds are formulated also as an optimization problem, which can be solved by using LMIs. Finally, a numerical example is given to illustrate the results.

关键词： Fault detection Large-scale systems Decentralized systems Threshold selection

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LS-SVM based neural controller as optimized by particle swarm algorithm using dual heuristic dynamic programming

LS-SVM based neural controller as optimized by particle swar...

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International Joint Conference on Neural Networks (IJCNN)

作者： Si-Yao Fu Guo-Sheng Yang Zeng-Guang Hou School of Information and Engineering Central University for Nationalities Beijing China Key laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China

The dual heuristic programming (DHP) approach has a superior ability for solving approximate dynamic programming problems in adaptive critic designs (ACD). The common approaches applied in the DHP are design the multilayer feedforward neural networks (MLFNN) as the differential model of the plant for training the critic and action networks. However, the problems of overfitting and premature convergence to local optima usually pose great challenges in the practice of MLFNNs during the training procedure. In this paper a least squares support vector machine (LS-SVM) regressor optimized by particle swarm algorithm (PSO) is proposed for generating the control actions and the learning rules for the critic and action networks. PSO is introduced to select the LS-SVM's hyper-parameters. The introduction of the SVM based training mechanism imparts the developed algorithm with inherent capacity for combating the overfitting problem as well as showing relatively high efficiency in converging to the optima. Simulation on the balancing of a cart pole plant shows that the proposed learning strategy is verified as faster convergence and higher efficiency as compared to traditional BP based adaptive dynamic programming approaches.

关键词： Particle swarm optimization Heuristic algorithms Dynamic programming Multi-layer neural network Convergence Support vector machines Least squares approximation Neural networks Feedforward neural networks Least squares methods

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Development and application of a data-driven fault prediction method to the imperial smelting furnace process

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IFAC Proceedings Volumes 2009年第8期42卷 1174-1179页

作者： Shaohua Jiang Weihua Gui S.X. Ding Amol Naik School of Information Science and Engineering Central South University Changsha 410083 China Institute for Automatic Control and Complex Systems University of Duisburg-Essen 47057 Duisburg Germany School of Computer Science Shaoguan University Shaoguan 512024 China

This paper addresses the development and application of a data-driven method to the fault diagnosis in imperial smelting furnace (ISF). Based on the method of the weighted least squares vector machines regression, a Hammerstein model is constructed and identified for the ISF. This model is used to predict the dynamic behavior of the furnace and the possible faults in the process. The simulation study shows that the identified model well adapts to the changes in the structural parameters and provides accurate prediction.

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Mixed model based SLAM approach for mobile robot

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2009年第SUPPL. 1期33卷 98-103页

作者： Fang, Fang Ma, Xu-Dong Dai, Xian-Zhong School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of CSE Complex Systems of Engineering Nanjing 210096 China

A new simultaneous localization and mapping approach based on mixed map model using laser data and odometry information is presented in this paper. Mixed model composed of occupancy grids and line maps is utilized to represent environment maps. At the same time Hough transform is introduced to extract line features. Then robot localization and map building task is accomplished using line features matching and extended Kalman filter. Experimental results indicate the feasibility and validity of this approach.

关键词： Extended Kalman filters

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Data-based Optimal control for Discrete-time Zero-sum Games of 2-D systems Using Adaptive Critic Designs

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Acta Automatica Sinica 2009年第6期35卷 682-692页

作者： Qing-Lai WEI Hua-Guang ZHANG Li-Li CUI The Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100190 P.R. China The School of Information Science and Engineering Northeastern University Shenyang 110004 P.R. China

In this paper, an iterative adaptive critic design (ACD) algorithm is proposed to solve a class of discrete-time two-person zero-sum games for Roesser type 2-D system. The idea is to use adaptive critic technique to obtain the optimal control pair iteratively to make the performance index function reach the saddle point of the zero-sum games. The proposed iterative ACD algorithm can be implemented based on the input and state data without the system model. Stability analysis of the 2-D system is presented and the convergence property of the performance index function is also proved. Neural networks are used to approximate the performance index function and compute the optimal control policies, respectively, for facilitating the implementation of the iterative ACD algorithm. The optimal control scheme of the air drying process is given to illustrate the performance of the proposed method.

关键词： Adaptive critic designs (ACD) optimal control zero-sum game 2-D system neural networks

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Sampled Data Errors-in-Variables systems

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IFAC Proceedings Volumes 2009年第10期42卷 1157-1162页

作者： Juan C. Agüero Graham C. Goodwin Torsten Söderström Juan I. Yuz ARC Centre for Complex Dynamics Systems and Control School of Electrical Engineering and Computer Science The University of Newcastle Australia Department of Information Technology Uppsala University Sweden Department of Electronic Engineering Universidad Técnica Federico Santa María Valparaíso Chile

Errors-in-Variables systems have been extensively studied in the literature. We study the impact of sampling on a continuous-time errors-in-variables problem. In particular, we study some approximations of a two dimensional (input-output) continuous-time signal spectrum developed from the sampled-data spectrum. Indeed, some of the paper is tutorial in nature. We also explore the possibility of retrieving the underlying continuous-time system from samples of the input and output signals.

关键词： Sampled-data models Errors-in-Variables Identifiability

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