26 resultados para System Identification

em Aston University Research Archive


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Methods of dynamic modelling and analysis of structures, for example the finite element method, are well developed. However, it is generally agreed that accurate modelling of complex structures is difficult and for critical applications it is necessary to validate or update the theoretical models using data measured from actual structures. The techniques of identifying the parameters of linear dynamic models using Vibration test data have attracted considerable interest recently. However, no method has received a general acceptance due to a number of difficulties. These difficulties are mainly due to (i) Incomplete number of Vibration modes that can be excited and measured, (ii) Incomplete number of coordinates that can be measured, (iii) Inaccuracy in the experimental data (iv) Inaccuracy in the model structure. This thesis reports on a new approach to update the parameters of a finite element model as well as a lumped parameter model with a diagonal mass matrix. The structure and its theoretical model are equally perturbed by adding mass or stiffness and the incomplete number of eigen-data is measured. The parameters are then identified by an iterative updating of the initial estimates, by sensitivity analysis, using eigenvalues or both eigenvalues and eigenvectors of the structure before and after perturbation. It is shown that with a suitable choice of the perturbing coordinates exact parameters can be identified if the data and the model structure are exact. The theoretical basis of the technique is presented. To cope with measurement errors and possible inaccuracies in the model structure, a well known Bayesian approach is used to minimize the least squares difference between the updated and the initial parameters. The eigen-data of the structure with added mass or stiffness is also determined using the frequency response data of the unmodified structure by a structural modification technique. Thus, mass or stiffness do not have to be added physically. The mass-stiffness addition technique is demonstrated by simulation examples and Laboratory experiments on beams and an H-frame.

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Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

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Product reliability and its environmental performance have become critical elements within a product's specification and design. To obtain a high level of confidence in the reliability of the design it is customary to test the design under realistic conditions in a laboratory. The objective of the work is to examine the feasibility of designing mechanical test rigs which exhibit prescribed dynamical characteristics. The design is then attached to the rig and excitation is applied to the rig, which then transmits representative vibration levels into the product. The philosophical considerations made at the outset of the project are discussed as they form the basis for the resulting design methodologies. It is attempted to directly identify the parameters of a test rig from the spatial model derived during the system identification process. It is shown to be impossible to identify a feasible test rig design using this technique. A finite dimensional optimal design methodology is developed which identifies the parameters of a discrete spring/mass system which is dynamically similar to a point coordinate on a continuous structure. This design methodology is incorporated within another procedure which derives a structure comprising a continuous element and a discrete system. This methodology is used to obtain point coordinate similarity for two planes of motion, which is validated by experimental tests. A limitation of this approach is that it is impossible to achieve multi-coordinate similarity due to an interaction of the discrete system and the continuous element at points away from the coordinate of interest. During the work the importance of the continuous element is highlighted and a design methodology is developed for continuous structures. The design methodology is based upon distributed parameter optimal design techniques and allows an initial poor design estimate to be moved in a feasible direction towards an acceptable design solution. Cumulative damage theory is used to provide a quantitative method of assessing the quality of dynamic similarity. It is shown that the combination of modal analysis techniques and cumulative damage theory provides a feasible design synthesis methodology for representative test rigs.

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In data envelopment analysis (DEA), operating units are compared on their outputs relative to their inputs. The identification of an appropriate input-output set is of decisive significance if assessment of the relative performance of the units is not to be biased. This paper reports on a novel approach used for identifying a suitable input-output set for assessing central administrative services at universities. A computer-supported group support system was used with an advisory board to enable the analysts to extract information pertaining to the boundaries of the unit of assessment and the corresponding input-output variables. The approach provides for a more comprehensive and less inhibited discussion of input-output variables to inform the DEA model. © 2005 Operational Research Society Ltd. All rights reserved.

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This thesis deals with the problem of Information Systems design for Corporate Management. It shows that the results of applying current approaches to Management Information Systems and Corporate Modelling fully justify a fresh look to the problem. The thesis develops an approach to design based on Cybernetic principles and theories. It looks at Management as an informational process and discusses the relevance of regulation theory to its practice. The work proceeds around the concept of change and its effects on the organization's stability and survival. The idea of looking at organizations as viable systems is discussed and a design to enhance survival capacity is developed. It takes Ashby's theory of adaptation and developments on ultra-stability as a theoretical framework and considering conditions for learning and foresight deduces that a design should include three basic components: A dynamic model of the organization- environment relationships; a method to spot significant changes in the value of the essential variables and in a certain set of parameters; and a Controller able to conceive and change the other two elements and to make choices among alternative policies. Further considerations of the conditions for rapid adaptation in organisms composed of many parts, and the law of Requisite Variety determine that successful adaptive behaviour requires certain functional organization. Beer's model of viable organizations is put in relation to Ashby's theory of adaptation and regulation. The use of the Ultra-stable system as abstract unit of analysis permits developing a rigorous taxonomy of change; it starts distinguishing between change with in behaviour and change of behaviour to complete the classification with organizational change. It relates these changes to the logical categories of learning connecting the topic of Information System design with that of organizational learning.

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Initially this thesis examines the various mechanisms by which technology is acquired within anodizing plants. In so doing the history of the evolution of anodizing technology is recorded, with particular reference to the growth of major markets and to the contribution of the marketing efforts of the aluminium industry. The business economics of various types of anodizing plants are analyzed. Consideration is also given to the impact of developments in anodizing technology on production economics and market growth. The economic costs associated with work rejected for process defects are considered. Recent changes in the industry have created conditions whereby information technology has a potentially important role to play in retaining existing knowledge. One such contribution is exemplified by the expert system which has been developed for the identification of anodizing process defects. Instead of using a "rule-based" expert system, a commercial neural networks program has been adapted for the task. The advantages of neural networks over 'rule-based' systems is that they are better suited to production problems, since the actual conditions prevailing when the defect was produced are often not known with certainty. In using the expert system, the user first identifies the process stage at which the defect probably occurred and is then directed to a file enabling the actual defects to be identified. After making this identification, the user can consult a database which gives a more detailed description of the defect, advises on remedial action and provides a bibliography of papers relating to the defect. The database uses a proprietary hypertext program, which also provides rapid cross-referencing to similar types of defect. Additionally, a graphics file can be accessed which (where appropriate) will display a graphic of the defect on screen. A total of 117 defects are included, together with 221 literature references, supplemented by 48 cross-reference hyperlinks. The main text of the thesis contains 179 literature references. (DX186565)

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Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented. © 2012 Inderscience Enterprises Ltd.

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A recently developed spectral method for identifying metastable states in Markov chains is used to analyse the conformational dynamics of a four residue peptide Valine-Proline-Alanine-Leucine. We compare our results to empirically defined conformational states and show that the found metastable states correctly reproduce the conformational dynamics of the system.

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The development of an information system in Caribbean public sector organisations is usually seen as a matter of installing hardware and software according to a directive from senior management, without much planning. This causes huge investment in procuring hardware and software without improving overall system performance. Increasingly, Caribbean organisations are looking for assurances on information system performance before making investment decisions not only to satisfy the funding agencies, but also to be competitive in this dynamic and global business world. This study demonstrates an information system planning approach using a process-reengineering framework. Firstly, the stakeholders for the business functions are identified along with their relationships and requirements. Secondly, process reengineering is carried out to develop the system requirements. Accordingly, information technology is selected through detailed system requirement analysis. Thirdly, cost-benefit analysis, identification of critical success factors and risk analysis are carried out to strengthen the selection. The entire methodology has been demonstrated through an information system project in the Barbados drug service, a public sector organisation in the Caribbean.

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Recently identified genes located downstream (3') of the msmEF (transport encoding) gene cluster, msmGH, and located 5' of the structural genes for methanesulfonate monooxygenase (MSAMO) are described from Methylosulfonomonas methylovora. Sequence analysis of the derived polypeptide sequences encoded by these genes revealed a high degree of identity to ABC-type transporters. MsmE showed similarity to a putative periplasmic substrate binding protein, MsmF resembled an integral membraneassociated protein, and MsmG was a putative ATP-binding enzyme. MsmH was thought to be the cognate permease component of the sulfonate transport system. The close association of these putative transport genes to the MSAMO structural genes msmABCD suggested a role for these genes in transport of methanesulfonic acid (MSA) into M. methylovora. msmEFGH and msmABCD constituted two operons for the coordinated expression of MSAMO and the MSA transporter systems. Reverse-transcription-PCR analysis of msmABCD and msmEFGH revealed differential expression of these genes during growth on MSA and methanol. The msmEFGH operon was constitutively expressed, whereas MSA induced expression of msmABCD. A mutant defective in msmE had considerably slower growth rates than the wild type, thus supporting the proposed role of MsmE in the transport of MSA into M. methylovora.

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The aim of this work was to design and build an equipment which can detect ferrous and non-ferrous objects in conveyed commodities, discriminate between them and locate the object along the belt and on the width of the belt. The magnetic induction mechanism was used as a means of achieving the objectives of this research. In order to choose the appropriate geometry and size of the induction field source, the field distributions of different source geometries and sizes were studied in detail. From these investigations it was found the square loop geometry is the most appropriate as a field generating source for the purpose of this project. The phenomena of field distribution in the conductors was also investigated. An equipment was designed and built at the preliminary stages of thework based on a flux-gate magnetometer with the ability to detect only ferrous objects.The instrument was designed such that it could be used to detect ferrous objects in the coal conveyors of power stations. The advantages of employing this detector in the power industry over the present ferrous metal electromagnetic separators were also considered. The objectives of this project culminated in the design and construction of a ferrous and non-ferrous detector with the ability to discriminate between ferrous and non-ferrous metals and to locate the objects on the conveying system. An experimental study was carried out to test the performance of the equipment in the detection of ferrous and non-ferrous objects of a given size carried on the conveyor belt. The ability of the equipment to discriminate between the types of metals and to locate the object on the belt was also evaluated experimentally. The benefits which can be gained from the industrial implementations of the equipment were considered. Further topics which may be investigated as an extension of this work are given.

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This thesis is concerned with the measurement of the characteristics of nonlinear systems by crosscorrelation, using pseudorandom input signals based on m sequences. The systems are characterised by Volterra series, and analytical expressions relating the rth order Volterra kernel to r-dimensional crosscorrelation measurements are derived. It is shown that the two-dimensional crosscorrelation measurements are related to the corresponding second order kernel values by a set of equations which may be structured into a number of independent subsets. The m sequence properties determine how the maximum order of the subsets for off-diagonal values is related to the upper bound of the arguments for nonzero kernel values. The upper bound of the arguments is used as a performance index, and the performance of antisymmetric pseudorandom binary, ternary and quinary signals is investigated. The performance indices obtained above are small in relation to the periods of the corresponding signals. To achieve higher performance with ternary signals, a method is proposed for combining the estimates of the second order kernel values so that the effects of some of the undesirable nonzero values in the fourth order autocorrelation function of the input signal are removed. The identification of the dynamics of two-input, single-output systems with multiplicative nonlinearity is investigated. It is shown that the characteristics of such a system may be determined by crosscorrelation experiments using phase-shifted versions of a common signal as inputs. The effects of nonlinearities on the estimates of system weighting functions obtained by crosscorrelation are also investigated. Results obtained by correlation testing of an industrial process are presented, and the differences between theoretical and experimental results discussed for this case;

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The work presents a new method that combines plasma etching with extrinsic techniques to simultaneously measure matrix and surface protein and lipid deposits. The acronym for this technique is PEEMS - Plasma Etching and Emission Monitoring System. Previous work has identified the presence of proteinaceous and lipoidal deposition on the surface of contact lenses and highlighted the probability that penetration of these spoilants will occur. This technique developed here allows unambiguous identification of the depth of penetration of spoilants to be made for various material types. It is for this reason that the technique has been employed in this thesis. The technique is applied as a 'molecular' scalpel, removing known amounts of material from the target. In this case from both the anterior .and posterior surfaces of a 'soft' contact lens. The residual material is then characterised by other analytical techniques such as UV/visible .and fluorescence spectroscopy. Several studies have be.en carried out for both in vivo and in vitro spoilt materials. The analysis and identification of absorbed protein and lipid of the substrate revealed the importance of many factors in the absorption and adsorption process. The effect of the material structure, protein nature (in terms of size, shape and charge) and environment conditions were examined in order to determine the relative uptake of tear proteins. The studies were extended to real cases in order to study the. patient dependent factors and lipoidal penetration.

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The thermal oxidation of two model compounds representing the aromatic polyamide, MXD6 (poly m-xylylene adipamide) have been investigated. The model compounds (having different chemical structures, viz, one corresponding to the aromatic part of the chain and the other to the aliphatic part), based on the structure of MXD6 were prepared and reactions with different concentrations of cobalt ions examined with the aim of identifying the role of the different structural components of MXD6 on the mechanism of oxidation. The study showed that cobalt, in the presence of sodium phosphite (which acts as an antioxidant for MXD6 and the model compounds), increases the oxidation of the model compounds. It is believed that the cobalt acts predominantly as a catalyst for the decomposition of hydroperoxides, formed during oxidation of the models in the melt phase, to free radical products and to a lesser extent as a catalyst for the initiation of the oxidation reaction by complex formation with the amide, which is more likely to take place in the solid phase. An oxidation cycle has been proposed consisting of two parts both of which will occur, to some extent under all conditions of oxidation (in the melt and in the solid phase), but their individual predominance must be determined by the prevailing oxygen pressure at the reaction site. The different aspects of this proposed mechanism were examined from extensive model compound studies, and the evidence based on the nature of product formation and the kinetics of these reactions. Main techniques used to compare the rates of oxidation and the study of kinetics included, oxygen absorption, FT-IR, UV and TGA. HPLC was used for product separation and identification.