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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： S. Wongsa V. Kadirkamanathan S.A. Billings P.C. Wright Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Department of Chemical and Process Engineering University of Sheffield Sheffield UK

In this work, the problem of metabolic flux estimation is formulated as a problem of parameter estimation from incomplete labelling data. The expectation/conditional maximisation (ECM) algorithm is used to determined a maximum-likelihood (ML) estimate because of its simplicity and stable convergence. We propose to simplify a nonlinear inverse problem, generally numerically solved by an iterative optimisation algorithm, to a linear regression problem which is arrived at from a linear-in-the-parameter formulation during a partial optimisation process of the ECM algorithm. Three linear least square algorithms, the ordinary least squares (LS), the total least squares (TLS) and the constrained least squares (CLS), have been tested to solve the linear regression in this step. Using simulations, resulting parameter estimates and errors in flux estimation are compared and evaluated. The performance of the algorithms are investigated under two scenarios; when the labelling data are corrupted by a wide range of noise and when the labelling data are incompletely observed. Results suggest that the estimates from the ECM algorithm using CLS produce results superior to other combinations and have potential to be refined to improve its performance in metabolic flux estimation

关键词： Labeling Iterative algorithms Least squares methods Electrochemical machining Parameter estimation Maximum likelihood estimation Linear regression Convergence Inverse problems Testing

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MODEL-BASED OPTIMISATION AND control OF THE HOT-ROLLING process FOR THE DESIGN OF STEEL MICROSTRUCTURE

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IFAC Proceedings Volumes 2007年第11期40卷 255-260页

作者： Miguel Angel Gama Mahdi Mahfouf IMMPETUS (Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield) Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield S1 3JD UK

A new integrated approach to carry-out advanced optimisation and control of the hot-rolling of steel is presented. The proposed design includes two stages: (1) OPTIMISATION: Genetic Algorithms and physically-based models describing the kinetics of dynamic microstructural behavior are used, along with an optimisation criterion, to set-up the optimal rolling schedule; (2) control: advanced control strategies, including Model-based Predictive control, are used to guarantee the optimal performance of the mill during the rolling process. The overarching aim of this research work is to integrate knowledge about both the stock and the rolling process to find optimal hot-deformation profiles and achieve the desired final steel microstructure and properties.

关键词： Steel Manufacture and Industry Predictive control Genetic Algorithms Optimisation

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FUZZY PREDICTIVE MODELLING USING HIERARCHICAL CLUSTERING AND MULTI-OBJECTIVE OPTIMISATION FOR MECHANICAL PROPERTIES OF ALLOY STEELS

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IFAC Proceedings Volumes 2007年第11期40卷 427-432页

作者： Qian Zhang Mahdi Mahfouf 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

In this paper, a systematic data-driven fuzzy predictive modelling mechanism is proposed. In this mechanism, a hierarchical clustering algorithm, the agglomerative complete-link clustering algorithm, is first employed to extract an initial fuzzy model. Then, the initial model is improved and optimised through a two-step operation using evolutionary algorithms (EAs), which takes into account both the accuracy and the interpretability performance of the fuzzy system. The proposed modelling approach is tested on a high dimensional problem using real data from the steel industry which concerns the prediction of the mechanical properties of alloy steels, in particular the Tensile Strength (TS). Experimental results show that the proposed approach is effective in eliciting accurate and interpretable models while ensuring their future easy maintenance.

关键词： Fuzzy modelling Model approximation Knowledge acquisition Multiobjective optimisations Mechanical properties Steel

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Tfe Solberg Award

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Naval Engineers Journal 2009年第5期112卷

作者： Dr. Roy L. Streit Since 1992 Dr. Streit has focused a significant amount of his energy to assignment problems in acoustic warfare data fusion systems. This work led him to the formulation of the PDD Principle a broadly useful theoretical method that enables the derivation of new classes of discrete-continuous estimation algorithms for solving assignment problems without requiring enumeration and pruning. In recognition of his outstanding work in this area Dr. Streit received the NAVSEA Scientist of the Year Award for 1997. Dr. Streit has also been pursuing avenues for analyzing the loss in broadband detection performance of an acoustic array in the presence of interferences. Because examining all possible separations between the signal and many interferers is infeasible he has proposed a Poisson process model for the number and location (s) of the interferers. In this same time period Dr. Streit has also been investigating issues in environmental modeling and localization by proposing a novel integral method for solving the bearings-only target motion analysis problem which enables a natural heuristic for compensating for mismatch between the model predictions and the real world. Most recently Dr. Streit has proposed the Numerical ACoustic Hull ARray (NACHAR) Project as a revolutionary and ambitious approach to hull array design. Its premise is that optimizing the detection capability of large hull arrays requires the full integration of hull sensor array and beamformer design processes. Because NACHAR crosses an unusual number of technical disciplines it involves researchers from several departments. The diversity of Dr. Streif s technical background makes him uniquely suited to lead the project Dr. Streifs truly impressive scientific achievements are complemented by a noteworthy list of professional activities that accentuate his value to Division Newport and the Navy. He represents the United States in The Technical Cooperation Program Maritime Activities Panel 9 (Sonar Technology) and participates in the Division New

for his significant engineering research and development in sonar array research and acoustic transient signals as set forth in the following

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AN EXTENDED 316L STAINLESS STEEL MODEL SUITABLE FOR INDUSTRIAL ROLLING

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IFAC Proceedings Volumes 2007年第11期40卷 305-310页

作者： M.F. Abbod M. Mahfouf D.A. Linkens C.M. Sellars IMMPETUS Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield School of Engineering and Design Brunel University West London UK Department of Automatic Control and Systems Engineering University of Sheffield UK Department of Engineering Materials University of Sheffield UK

During hot rolling processes, the material under deformation undergoes different deformation conditions, i.e. temperature changes and strain rates. One particular variable is the change in strain rate which can vary from low to very high values in industrial rolling. Usually empirical models are used for predicting the material characteristics but they are only valid within constrained limits. In this work an extended model has been developed to predict the stress/strain characteristics of 316L stainless steel material under a wider range of deformation conditions, i.e. high strain rates changes which do not follow the equation-of-states laws.

关键词： 316L stainless steel dynamic recrystallisation non-equation-of-states strain rate plane strain compression test

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MULTI-MODAL SIMULATION FOR MICROSTRUCTURAL AND PROPERTY PREDICTION FOR AL ALLOY HOT ROLLING

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IFAC Proceedings Volumes 2007年第11期40卷 119-124页

作者： D.A. Linkens T Wong M.F. Abbod M. Mahfouf J. Talamantes-Silva IMMPETUS Institute for Microstructural and Mechanical Process Engineering The University of Sheffield Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK School of Engineering and Design Brunel University UK Sheffield Forgemasters UK

This study presents the application of FE modelling and intelligent systems techniques to the prediction of microstructural mapping for aluminium alloys. Here, the material within each finite element is defined using a set of non-linear physically-based equations. These are then solved in real-time using a semi-physical grey-box model. This model is based on a neuro-fuzzy approach and it has been embedded within the FE technique. The model maps the evolution of the internal state variables (i.e. dislocation density, subgrain size and subgrain boundary misorientation) and their effect on the recrystallisation behaviour of the stock. This paper presents the model development, the integration between the numerical techniques, and the application of the technique to a hot rolling operation using an Aluminium, 1wt% Magnesium alloy. In addition, the developed model includes a CA (Cellular Automata) level to represent inhomogeneous nature of microstructural beheviour.

关键词： hybrid modelling finite element hot rolling neuro-fuzzy microstructure recrystallisation

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Hot Rolled Aluminium Alloys Texture via Hybrid Modelling

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IFAC Proceedings Volumes 2007年第11期40卷 437-442页

作者： M. Mahfouf D.A. Linkens M.F. Abbod J. Talamantes-Silva IMMPETUS Institute for Microstructural and Mechanical Process Engineering The University of Sheffield Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK School of Engineering and Design Brunel University UK Sheffield Forgemasters UK

During the thermomechanical processing of aluminium alloys, the material experiences a complex history of temperature, time, and strain path. The rolling and deformation process has an effect on the evolution of the material texture which can be modelled using finite element models of the rolling process and a Taylor model for texture evolution. This paper explores the potential of modelling the rolling and texture evolution processes using data-driven systems models to reduce the computational time and achieve better accuracy.

关键词： aluminium alloys texture hybrid modelling

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A Paradigm for the Scheduling of a Continuous Walking Beam Reheat Furnace Using a Modified Genetic Algorithm

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Materials & Manufacturing processes 2007年第5期22卷 607-614页

作者： Broughton, Jonathan S. Mahfouf, Mahdi m.mahfouf@ sheffield.ac.uk Linkens, Derek A. Department of Long Product Rolling CORUS-UK Ltd. Swinden Technology Centre Moorgate Rotherham South Yorkshire UK Department of Automatic Control and Systems Engineering Institute for Microstructural and Mechanical Process Engineering The University of Sheffield (IMMPETUS) Sheffield UK

The paper discusses the application of a paradigm for creating scheduling systems for steel reheating furnaces. The proposed paradigm utilizes a modified version of a Genetic Algorithm (GA) to optimize such schedules via new ways of realizing the crossover and mutation operations. The work was conducted in collaboration with the Thrybergh Combination Mill owned by CORUS- Sheffield (UK). The outcome of this research work is a novel scheduling system which links together the scheduling and furnace controls and is also able to accept new and already established mill heuristics. The proposed methodology is 'flexible' as well as 'generic' as it can be augmented easily in order to suit other industrial set-ups. [ABSTRACT FROM AUTHOR]

关键词： Optimization Reheat furnace Scheduling Simulation Time-delay

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An Agent Matching Architecture for Bilateral Contacts in Multi Agent Markets

An Agent Matching Architecture for Bilateral Contacts in Mul...

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IEEE International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Hamed Kebriaei Vahid Johari Majd Ashkan Rahimi-Kian Intelligent Control Systems Lab. Electrical Engineering Dept. Tarbiat Modares University Tehran Iran Intelligent Control Systems Laboratory Electrical Engineering Department Tarbiat Moalem University Tehran Iran Control and Intelligent Process Center of Excellence Electrical Engineering Department University of Tehran Tehran Tehran Iran

In this paper, an agent matching architecture for bilateral contracts of a multi agent market is proposed. The bilateral market contains a number of sellers and buyers who face opponents for negotiation and signing bilateral contracts. Each agent has a hierarchical representation of trading commodity attributes, where based on that it will create a tree structure of attributes. Using this structure, we apply a modified version of fuzzy similarity algorithm to compute similarity between each pair of buyer and seller agents' trees. Then, we use game theory and the concept of Stackelberg equilibrium to assess the matchmaking among the seller and buyer agents. Agents who lose contract or want to sign a new contract have a chance to restart the procedure. Through a case study for bilateral contracts in energy market, the applicability of our agent matching architecture is illustrated.

关键词： Contracts Game theory Tree data structures Decision making Contacts Intelligent control Intelligent agent control systems Supply and demand Fuzzy sets

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Special Issue on Variable Structure System control — New Designs and Applications

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Asian Journal of control 2008年第4期5卷

作者： Prof. Jian-Xin Xu Prof. Leonid Fridman Department of Electrical and Computer Eng. National University of Singapore 4 Engineering Drive 3 Singapore 117576 Tel +65 6874-2566 Fax +65 6779-1103 Dr Jian-Xin Xu received his Bachelor degree from Zhejiang University China in 1982. He attended the University of Tokyo Japan where he received his Master's and Ph.D. degrees in 1986 and 1989 respectively. All his degrees are in Electrical Engineering. He worked for one year in the Hitachi research Laboratory Japan and for more than one year in Ohio State University U.S.A. as a Visiting Scholar. In 1991 he joined the National University of Singapore and is currently an associate professor in the Department of Electrical Engineering. His research interests lie in the fields of learning control variable structure control fuzzy logic control discontinuous signal processing and applications to motion control and process control problems. He is the associate editor of Asian Journal of Control member of TC on variable structure systems and sliding mode control of IEEE Control Systems Society and a senior member of IEEE. He has produced more than 90 peer-refereed journal papers near 160 technical papers in conference proceedings and authored/edited 4 books. Division de Estudios de Posgrado Facultad de Ingenieria National Autonomous University of Mexico DEP-FI UNAM Edificio “A” Circuito Exterior Ciudad Universitaria A. P. 70–256 C.P.04510 Mexico D.F. Mexico Tel +52 55 56223014 Fax +52 55 56161719 Dr. Leonid M. Fridman received his M.S in mathematics from Kuibyshev (Samara) State University Russia Ph.D. in Applied Mathematics from Institute of Control Science (Moscow) and Dr. of Science degrees in Control Science from Moscow State University of Mathematics and Electronics in 1976 1988 and 1998 respectively. In 1976–1999 Dr. Fridman was with the Department of Mathematics at the Samara State Architecture and Civil Engineering Academy Samara Russia. In 2000–2002 he was with the Department of Postgraduate Study and Investigations at the Chihuahu

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