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An immune inspired approach to 802.11 Wireless LANs coverage optimization

An immune inspired approach to 802.11 Wireless LANs coverage...

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International Conference on Information Networking and Automation (ICINA)

作者： Xuan Zhou Rongbin Qi Qian Li Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Electronics and Information University of Tongji Shanghai China

ISBN: (纸本)9781424481040

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that opt-aiNet is an effective way to optimize the 802.11 Wireless LANs planning problems.

关键词： education Gallium Indexes Computational modeling

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On Line Estimation of Color Values (B*) In Pet process Using Gaussian process Regression

On Line Estimation of Color Values (B*) In Pet Process Using...

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The 8th World Congress on Intelligent control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Na Luo Feng Qian School of Information Science and Engineering Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 P.R.China

With improvement of PET quality, the color of PET is required to be controlled. But the mechanism model of PET color is not so clear. In this paper, a modeling method of color values (B*) is introduced. It is based on sparse pseudo-input gaussian process. Online correction is added to the modeling based on sliding time window. Comparing to support vector regression, the model using gaussian process gives both prediction and predictive variance. The results show that B* value model using gaussian process is more flexible and can be used in real process.

关键词： Positron emission tomography Color Joints

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Reduced-order multiple models robust direct adaptive control of non-minimum phase system

Reduced-order multiple models robust direct adaptive control...

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World Congress on Intelligent control and Automation (WCICA)

作者： J.-Z. Liu Z.-L. Wang Xin Wang D.-H. Wang Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Center of Electrical & Electronic Engineering Shanghai Jiaotong University Shanghai China

The performance of robust adaptive control system based on traditional revised algorithm is awful in the presence of unmodeled dynamics and the performance will go bad, even be unstable, when the working condition (including the parameter, reference input, and so on) change. This paper designs the multiple models robust adaptive controller to control the discrete single-variable non-minimum phase system. First, the higher part of the system is deem to be the unmodelled dynamic and the normalization is introduced to convert the system unmodeled dynamics to bounded disturbance as well as the dead zone is introduced in parameter update algorithm. And then, the multiple models robust adaptive controllers are designed based on the lower part of the system and the best controller is chosen based on the switch index to control the system. The last simulation illustrates that the proposed method is preferable even the working condition changes.

关键词： Adaptation model Adaptive control Robustness Heuristic algorithms Switches

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Estimation of component concentrations of sodium aluminate solution via PLS and Hammerstein recurrent neural networks

Estimation of component concentrations of sodium aluminate s...

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International Workshop on advanced Computational Intelligence (IWACI)

作者： Wei Wang Lijie Zhao Tianyou Chai Wen Yu Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University China Key Laboratory of Integrated Automation of Process Industry Shenyang Institute of Chemical Technology Information Engineering School Ministry of Education China Key Laboratory of Integrated Automation of Process Industry Ministry of Education and Research Center of Automation Northeastern University China Departamento de Control Automatico CINVESTAV Mexicali Mexico

In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment results show that the proposed soft sensing algorithm is effective.

关键词： Nonlinear dynamical systems Recurrent neural networks Computational modeling Heuristic algorithms Temperature measurement Data models Artificial neural networks

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Evaluation of R&D projects with uncertainty based on evidence reasoning

Evaluation of R&D projects with uncertainty based on evidenc...

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International Conference on Logistics Systems and Intelligent Management (ICLSIM)

作者： Ying Yang Bengong Yu Lei Fu Haojie Shen Key Laboratory of Process Optimization & Intelligent Decision-making of Ministry of Education School of Management Hefei University of Technology Hefei China Chery Automobile Company Limited Wuhu China

This paper presents an assessment model for research and development (R&D) projects considering uncertainty in their overall life cycle. technology maturity and competitive advantages were considered and a Balanced Scorecard (BSC) model was developed to evaluate R&D projects. Based on the multilevel evaluation framework, an evidence reasoning approach has been developed to aggregate the numerical data and qualitative information with uncertainty. The expected utility is applied to describe preferences of decision-makers in the decision process. A case study in the context of automobile R&D projects is given to illustrate the methods.

关键词： Uncertainty Research and development Automobiles Aggregates Data envelopment analysis Laboratories Decision making technology management educational technology Electronic mail

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Fuzzy dynamic characteristic modeling and intelligent adaptive control for complex spacecraft

Fuzzy dynamic characteristic modeling and intelligent adapti...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xiong Luo Song Hu Zengqi Sun Xintao Qiu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristic modeling and control approach is an effective way to solve this problem. Aimed at the flexible satellites described by using characteristic modeling approach, with the help of fuzzy rules, fuzzy dynamic characteristic modeling method and intelligent adaptive controller are designed to control this complex spacecraft. Meanwhile, based on the satellite system simulation platform, we validate the correctness and efficiency of the proposed modeling and control method by comparing with the simulation results of the other similar methods.

关键词： Adaptation model Laboratories Satellites Space vehicles Intelligent control Artificial intelligence Information science

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Dynamic modeling and tracking control of fuel filled space robotic system with flexible manipulators

Dynamic modeling and tracking control of fuel filled space r...

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International Symposium on Systems and control in Aerospace and Astronautics (ISSCAA)

作者： Xinxin Yang Xiong Luo Fuchun Sun Fengge Wu Huaping Liu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and TechnologyTsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

In recent years, dynamics model and control of space robot system are the hot topics in the research field. In this paper, a new dynamics model and control strategy of space robotic system with a flexible manipulator and a liquid fuel tank are investigated. Based on Lagrange equation method, the dynamics model of the space robotic system coupling with liquid sloshing, flexibility vibration and base movement is derived. The elastic deflection of the flexible manipulator is described by the assumed mode method and equivalent mechanical model is adopted instead of liquid sloshing under the environment of low-gravity. The inverse dynamics control algorithm combined with PD control method is performed to solve the trajectory tracking problem. Some simulation results are given to verify the effectiveness of the proposed method.

关键词： Mathematical model Aerospace electronics Manipulator dynamics Equations Space vehicles

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Soft sensor modeling of ball mill load via principal component analysis and support vector machines

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7th International Symposium on Neural Networks, ISNN 2010

作者： Tang, Jian Zhao, Lijie Yu, Wen Yue, Heng Chai, Tianyou Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110819 China College of Information Engineering Shenyang Institute of Chemical Technology Shenyang 110142 China Departamento de Control Automatico CINVESTAV-IPN Av.IPN 2508 México D.F. 07360 Mexico

ISBN: (纸本)9783642129896

In wet ball mill, measurement accuracy of mill load (ML) is very important. It affects production capacity and energy efficiency. A soft sensor method is proposed to estimate the mill load in this paper. Vibration signal of mill shell in time domain is first transformed into power spectral density (PSD) using fast Fourier transform (FFT), such that the relative amplitudes of different frequencies contain mill load information directly. Feature variables at low, medium and high frequency bands are extracted through principal component analysis (PCA), which selects input as a preprocessing procedure to improve the modeling performance. Three support vector machine (SVM) models are built to predict the mill operating parameters. A case study shows that proposed soft sensor method has higher accuracy and better predictive performance than the other normal approaches. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Principal component analysis

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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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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Zhao, Lijie Tang, Jian Yu, Wen Yue, Heng Chai, Tianyou College of Information Engineering Shenyang University of Chemical Technology Shenyang I10142 China Key Laboratory of Integrated Automation of Process Industry Northeastern University Ministry of Education Shen yang Liaoning China Departamento de Control Automatico CINVESTAV-IPN Av.IPN 2508 México D.F. 07360 Mexico

ISBN: (纸本)9781424464388

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. © 2010 IEEE.

关键词： Genetic algorithms

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Dual perturbation AGC design based on QFT/μ controller in hot strip rolling process

Dual perturbation AGC design based on QFT/μ controller in h...

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Chinese control Conference (CCC)

作者： Ming Zhang Weidong Yang Shaofu Wang Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing P. R. China Laiwu Steel Corporation Laiwu P. R. China

The application of u-synthesis controller based on Quantitative Feedback Theory (QFT) tuning method in hot rolling Automatic Gauge control (AGC) system is delivered in this paper. In the proposed strategy, a renowned dual-perturbation AGC model is presented. To the stiffness uncertainties and nonlinear parts, the integration of optimal control μ-synthesis and manual tuning in the QFT design environment enable controller design with a high level of robust performance and robust stability. QFT's open-loop tuning can be more transparent than closed-loop tuning in industrial field. The simulation results show the combined controller is of better gauge control response and more effective on disturbance attenuation.

关键词： Robustness Tuning process control Uncertainty Mathematical model Strips control systems

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