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International Conference on Computational Intelligence, Modelling and Simulation (CSSIM)

作者： Wiem Jebri Jemai Houssem Jerbi Mohamed Naceur Abdelkrim High School of Engineering Gab ès. Analysis and Control of Energy Systems Inc. Tunisia Laboratory of Study and Automatic Control''s Process Tunisia

In this paper, we have developed a new approach to determine a feedback control law of a nonlinear input affine system by the use of efficient mathematical tools: the Kronecker product, the non-redundant state formulation and the polynomial representation of the transformation to a reference linear model, as well as a polynomial form of the control law. This method consists, as first step, in determining a polynomial transformation of coordinates to an equivalent linear model. Then, the synthesis of an analytic feedback control law via this nonlinear transformation has been presented in the second method step. The advantage of the proposed approach is the convenience of its implementation, as it copes with the complex differential geometric formalism of the exact linearization feedback control. To illustrate the efficiency of the presented approach, we have been applied it to a second order nonlinear model whose simulations results are presented.

关键词： control system synthesis Feedback control Nonlinear control systems Polynomials Mathematical model Linear feedback control systems Computational modeling Automatic control control systems Computational intelligence

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Tensile Strength Prediction for Hot Rolled Steels by Bayesian Neural Network Model

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IFAC Proceedings Volumes 2009年第23期42卷 255-260页

作者： Yong Y. Yang Mahdi Mahfouf Derek A. Linkens Qian Zhang Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield (IMMPETUS) Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK

A neural network model under the Bayesian framework (referred to as Bayesian neural network hereafter) is developed to predict the tensile strength of hot rolled products. The motivation of using a data-driven model is that in a modern steel mill, there exist huge online measurements and offline data, and can be exploited to extract the underlying relationships. The main advantage of using Bayesian neural network (BNN) is the robustness against over-fitting, thanks to the probabilistic reasoning behind the BNN. Preliminary modelling results are encouraging, and the properly trained BNN model can be used for online control and optimisation of the rolling mill to achieve desired mechanical properties.

关键词： Neural networks Bayesian technique steel hot rolling modelling tensile strength

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Modelling Charpy Impact Energy of Heat-Treated-Steel using Efficient Neural-Networks & Genetic-Algorithms

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IFAC Proceedings Volumes 2009年第23期42卷 237-242页

作者： Mahdi Mahfouf Yong Y. Yang Qian Zhang Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield (IMMPETUS) Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK

Although neural networks (NN) are known to represent a powerful tool for mapping non-linear relationships between the inputs and outputs, their structures are typically set up by the modeller either by trial-and-error or based on their own experience. The latter is not only a time-consuming operation but also creates a risk that the best model structure is not necessarily selected. In this paper a genetic algorithm (GA) based strategy of determining the optimal NN-based model structure, together with the best training options for NN modelling will be described. Initial results of this GA-NN based modelling paradigm are promising, with the model performance being significantly improved when compared to previously elicited where the model structures were defined in an ‘ad-hoc’ fashion.

关键词： Neural networks Genetic algorithms Steel Charpy impact energy Mechanical properties

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Characterisation of Model Error for Charpy Impact Energy of Heat Treated Steels Using Probabilistic Reasoning and a Gaussian Mixture Model

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IFAC Proceedings Volumes 2009年第23期42卷 225-230页

Data-driven modelling has gained much momentum recently, with modelling algorithms being evolved into more complex structures capable of dealing with highly non-linear multi-dimensional systems. However, it is widely accepted that data-driven models are typically obtained under the principle of error minimisation, with the assumption of normal error distribution. The latter assumption is often not valid in more complex modelling environments, leading to sub-optimal model predictions. In this paper, a new modelling strategy aimed at exploiting the rich information contained in the model error data using a Gaussian mixture model (GMM) is proposed. The GMM error model can provide a probability characterisation of the error distribution, which can then be used complementally with the original data model. This combination often produces improvements in prediction performances, as will be illustrated in the case study relating to the hybrid modelling of the Charpy impact energy of heat-treated steels.

关键词： Data-driven modelling hybrid modelling probabilistic reasoning Gaussian mixture model EM algorithm Charpy impact energy

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Input Weighted Data Granulation Using Hybrid Correlation Measures With Application to Metal Properties

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IFAC Proceedings Volumes 2009年第23期42卷 272-277页

作者： George Panoutsos Mahdi Mahfouf Qian Zhang Sid-Ahmed Gaffour Institute for Microstructural and Mechanical Process Engineering The University of Sheffield (IMMPETUS) Department of Automatic Control & Systems Engineering Amy Johnson Building Mappin Street Sheffield S1 3JD UK

This paper introduces a new data granulation algorithm using significance weights on the input space of the data set. This data granulation algorithm aims to provide a more reliable way of grouping data together by directing the data granulation to favor the most significant variables of the process under investigation. Such a data granulation algorithm assists in the elicitation of the initial rule-base of a fuzzy or neural-fuzzy model. A hybrid correlation index, called Significance Index, is introduced to rank the process variables based on the linear correlation coefficient and the partial correlation measure. The new algorithm is used to classify the process variables and subsequently model and predict mechanical properties of heat treated steel. The property under investigation is the Tensile Strength and the case study data set consists of chemical composition and microstructure measurements coupled with Tensile Strength measurements.

关键词： Input selection classification granular computing (GrC) data granulation granular-neural-fuzzy modelling material properties heat treatment tensile strength

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Sophisticated methodology of dummy pattern generation for suppressing dislocation induced contact misalignment on flash lamp annealed eSiGe wafer

Sophisticated methodology of dummy pattern generation for su...

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Symposium on VLSI Technology

作者： O. Fujii T. Sanuki Y. Oshiki T. Itani T. Kugimiya N. Nakamura M. Tamura T. Sato I. Mizushima H. Yoshimura M. Iwai F. Matsuoka Japan Toshiba Corporation Yokohama Japan System LSI Division Process and Manufacturing Engineering Center Yokohama Japan Semiconductor Company Research and Development Center Yokohama Japan ESS Division Toshiba Information Systems Corporation Yokohama Japan

Defects-induced contact misalignment when combining embedded SiGe with flash lamp annealing (FLA) on high performance 40 nm CMOS process has been analyzed both by experiments and novel dislocation loop dynamics simulation. We have found that slips which are created at the SiGe dummy patterns worsen the contact misalignment for the first time. Design guide lines on shape of SiGe patterns for slip free condition have been investigated and clarified. With optimized SiGe patterns, random component of contact misalignment have been successfully reduced to lead high SRAM yields at 40 nm tech node with high performance.

关键词： Lamps Silicon germanium Germanium silicon alloys Temperature Capacitive sensors Random access memory Simulated annealing Etching Thermal stresses Lattices

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Nanotechnology applications for clean water /

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2009年

作者： edited by Nora Savage ... [et al.].

来源：内蒙古大学图书馆图书评论

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Intrinsic relation between categorisation of food products and processes

Intrinsic relation between categorisation of food products a...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： H. Wurdemann V. Aminzadeh J.S. Dai G. Purnell J. Reed Division of Engineering The Centre of Mechatronics & Manufacturing Systems King's College London University of London London UK Food Refrigeration and Process Engineering Research Centre Churchill Building University of Bristol Bristol Somerset UK Silsoe Technology Limited Bedford UK

A possible area of applying new technology in food industry is food handling. Because food products vary even within the same product type, the most important step is the categorisation of different food goods. The improved and novel food classification, which will be discussed in this paper, is unambiguous and it is able to interpret the categorisation table in an engineering way. The overall purpose of food categorisation is to allocate each category to a certain food process that describes physical structure from disarray. Having the mathematical algorithms that depend on the input disarray, the output array and the food product category appropriate and specialised equipment can be used to lead products into order. This can be described in a 3-dimensional matrix.

关键词： Food products Food industry Temperature Robotics and automation Service robots Shape Food technology Manufacturing industries Mechatronics Manufacturing systems

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A Study of a Gun-Turret Assembly in an Armored Tank using Model Predictive control

A Study of a Gun-Turret Assembly in an Armored Tank using Mo...

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2009 American control Conference (ACC 2009)

作者： Gautam Kumar Pradeep Y. Tiwari Vincent Marcopoli Mayuresh V. Kothare Chemical Process Modeling and Control Center Department of Chemical Engineering Lehigh University Bethlehem PA 18015 U.S.A. Process Dynamics and Optimization group Bayer Technology Services Americas 8500 W Bay Rd Baytown TX 77523 U.S.A. General Dynamics Land Systems Sterling Hts. MI 48310 U.S.A.

ISBN: (纸本)9781424445233

Operation of the gun/turret system in a military tank is limited by several constraints some of which are posed by obstacles existing on the vehicle's own platform. These mechanical constraints acting as hard constraints can cause serious damage to the whole assembly if violated. A control strategy developed for such a system must avoid possible collision of the gun/turret system with these obstacles. We propose to use a MPC based control strategy, due to its inherent ability to handle constraints, for the deck clearance problem and evaluate its performance under operating conditions for a linear model of the tank. Matlab~R based MPCtoolbox is used to set up the MPC calculations for the gun/turret system. Simulations are performed to investigate and compare the performance of the controller under various deck constraint limits. It is shown that MPC is effective in addressing both the stabilization and deck clearance objectives.

关键词： Maximum Allowable Concentration control strategy Tanks belted distributed model predictive control nonlinear model predictive control Constraint Model predictive control Predictive control linear models Addressing assemblies Operating conditions vehicle controllers

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Stable multiple model adaptive control of nonlinear multivariable discrete-time systems

Stable multiple model adaptive control of nonlinear multivar...

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2009 American control Conference (ACC 2009)

作者： Yue Fu Tianyou Chai Hong Wang Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang Liaoning Province 110004 China Control Systems Center School of Electrical and Electronic Engineering The University of Manchester M60 1QD Manchester The United Kingdom

ISBN: (纸本)9781424445233

In this paper, to further relax the restriction on the higher order nonlinearity in [7], a stable multiple model adaptive control (SMMAC) method is developed. First a new robust adaptive controller is designed, which can guarantee the stability of the closed-loop system. Then to improve the system performance, the SMMAC method is presented by switching between the robust adaptive controller and a conventional neural network (NN) adaptive controller. Theory analysis and simulation results are presented to show the effectiveness of the proposed method.

关键词： adaptive controller adaptive control System performance higher-order nonlinearity Multivariable Induction loop systems stalls(animals)

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