On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Minimum-uncertaity states and pseudoclassical dynamics. II

The set of initial conditions for which the pseudoclassical evolution algorithm (and minimality conservation) is verified for Hamiltonians of degrees N (N>2) is explicitly determined through a class of restrictions for the corresponding classical trajectories, and it is proved to be at most denumerable. Thus these algorithms are verified if and only if the system is quadratic except for a set of measure zero. The possibility of time-dependent a-equivalence classes is studied and its physical interpretation is presented. The implied equivalence of the pseudoclassical and Ehrenfest algorithms and their relationship with minimality conservation is discussed in detail. Also, the explicit derivation of the general unitary operator which linearly transforms minimum-uncertainty states leads to the derivation, among others, of operators with a general geometrical interpretation in phase space, such as rotations (parity, Fourier).

Methodology for wind turbine blade geometry optimization

Nowadays, the upwind three bladed horizontal axis wind turbine is the leading player on the market. It has been found to be the best industrial compromise in the range of different turbine constructions. The current wind industry innovation is conducted in the development of individual turbine components. The blade constitutes 20-25% of the overall turbine budget. Its optimal operation in particular local economic and wind conditions is worth investigating. The blade geometry, namely the chord, twist and airfoil type distributions along the span, responds to the output measures of the blade performance. Therefore, the optimal wind blade geometry can improve the overall turbine performance. The objectives of the dissertation are focused on the development of a methodology and specific tool for the investigation of possible existing wind blade geometry adjustments. The novelty of the methodology presented in the thesis is the multiobjective perspective on wind blade geometry optimization, particularly taking simultaneously into account the local wind conditions and the issue of aerodynamic noise emissions. The presented optimization objective approach has not been investigated previously for the implementation in wind blade design. The possibilities to use different theories for the analysis and search procedures are investigated and sufficient arguments derived for the usage of proposed theories. The tool is used for the test optimization of a particular wind turbine blade. The sensitivity analysis shows the dependence of the outputs on the provided inputs, as well as its relative and absolute divergences and instabilities. The pros and cons of the proposed technique are seen from the practical implementation, which is documented in the results, analysis and conclusion sections.

Identificazione dei parametri meccanici del ponte metallico ferroviario a Pontelagoscuro attraverso un algoritmo di ottimizzazione di tipo evolutivo

Nel periodo storico compreso tra la seconda metà dell’Ottocento ed il primo ventennio del Novecento, un’ondata di innovazioni tecnologiche e scientifiche, unitamente all’espansione dell’industria siderurgica e la conseguente diffusione del ferro come materiale da costruzione, portarono alla realizzazione di strutture metalliche grandiose. Ciò fu reso possibile grazie ad una fervida attività di ricerca che permise la risoluzione di problematiche tecniche di assoluto rilievo, come la progettazione di grandi coperture o di ponti destinati al traffico ferroviario in grado di coprire luci sempre maggiori. In questo contesto si sviluppò il sistema della chiodatura come metodo di unione per il collegamento rigido e permanente dei vari elementi che compongono la struttura portante metallica. Ad oggi il sistema della chiodatura è stato quasi completamente sostituito dalla bullonatura di acciaio ad alta resistenza e dalla saldatura, che garantendo gli stessi standard di affidabilità e sicurezza, offrono vantaggi in termini economici e di rapidità esecutiva. Tuttavia lo studio delle unioni chiodate continua a rivestire notevole importanza in tutti quei casi in cui il progettista debba occuparsi di restauro, manutenzione o adeguamento di strutture esistenti che in molti casi continuano ad assolvere le funzioni per le quali erano state progettate. La valutazione delle strutture esistenti, in particolare i ponti, ha assunto un’importanza sempre crescente. L’incremento della mobilità e del traffico sulle infrastrutture di trasporto ha portato ad un incremento contemporaneo di carichi e velocità sui ponti. In particolare nelle ferrovie, i ponti rappresentano una parte strategica della rete ferroviaria e in molti casi, essi hanno già raggiunto i loro limiti di capacità di traffico, tanto è vero che l’età media del sessanta percento dei ponti metallici ferroviari è di un centinaio di anni. Pertanto i carichi di servizio, i cicli di sforzo accumulati a causa dei carichi da traffico e il conseguente invecchiamento delle strutture esistenti, inducono la necessità della valutazione della loro rimanente vita a fatica. In questo contesto, la valutazione delle condizioni del ponte e le conseguenti operazioni di manutenzione o sostituzione diventano indispensabili. Negli ultimi decenni sono state effettuate numerose iniziative di ricerca riguardo il comportamento a fatica dei ponti ferroviari chiodati, poiché le passate esperienze hanno mostrato che tali connessioni sono suscettibili di rotture per fatica. Da uno studio dell’ASCE Committee on Fatigue and Fracture Reliability è emerso che l’ottanta, novanta percento delle crisi nelle strutture metalliche è da relazionarsi ai fenomeni di fatica e frattura. Il danno per fatica riportato dai ponti chiodati è stato osservato principalmente sulle unioni tra elementi principali ed è causato dagli sforzi secondari, che si possono sviluppare in diverse parti delle connessioni. In realtà riguardo la valutazione della fatica sui ponti metallici chiodati, si è scoperto che giocano un ruolo importante molti fattori, anzitutto i ponti ferroviari sono soggetti a grandi variazioni delle tensioni indotte da carichi permanenti e accidentali, così come imperfezioni geometriche e inclinazioni o deviazioni di elementi strutturali comportano sforzi secondari che solitamente non vengono considerati nella valutazione del fenomeno della fatica. Vibrazioni, forze orizzontali trasversali, vincoli interni, difetti localizzati o diffusi come danni per la corrosione, rappresentano cause che concorrono al danneggiamento per fatica della struttura. Per questo motivo si studiano dei modelli agli elementi finiti (FE) che riguardino i particolari delle connessioni e che devono poi essere inseriti all’interno di un modello globale del ponte. L’identificazione degli elementi critici a fatica viene infatti solitamente svolta empiricamente, quindi è necessario che i modelli numerici di cui si dispone per analizzare la struttura nei particolari delle connessioni, così come nella sua totalità, siano il più corrispondenti possibile alla situazione reale. Ciò che ci si propone di sviluppare in questa tesi è un procedimento che consenta di affinare i modelli numerici in modo da ottenere un comportamento dinamico analogo a quello del sistema fisico reale. Si è presa in esame la seguente struttura, un ponte metallico ferroviario a binario unico sulla linea Bologna – Padova, che attraversa il fiume Po tra le località di Pontelagoscuro ed Occhiobello in provincia di Ferrara. Questo ponte fu realizzato intorno agli anni che vanno dal 1945 al 1949 e tra il 2002 e il 2006 ha subito interventi di innalzamento, ampliamento ed adeguamento nel contesto delle operazioni di potenziamento della linea ferroviaria, che hanno portato tra l’altro all’affiancamento di un nuovo ponte, anch’esso a singolo binario, per i convogli diretti nella direzione opposta. Le travate metalliche del ponte ferroviario sono costituite da travi principali a traliccio a gabbia chiusa, con uno schema statico di travi semplicemente appoggiate; tutte le aste delle travi reticolari sono formate da profilati metallici in composizione chiodata. In particolare si è rivolta l’attenzione verso una delle travate centrali, della quale si intende affrontare un’analisi numerica con caratterizzazione dinamica del modello agli Elementi Finiti (FEM), in modo da conoscerne lo specifico comportamento strutturale. Ad oggi infatti l’analisi strutturale si basa prevalentemente sulla previsione del comportamento delle strutture tramite modelli matematici basati su procedimenti risolutivi generali, primo fra tutti il Metodo agli Elementi Finiti. Tuttavia i risultati derivanti dal modello numerico possono discostarsi dal reale comportamento della struttura, proprio a causa delle ipotesi poste alla base della modellazione. Difficilmente infatti si ha la possibilità di riscontrare se le ipotesi assunte nel calcolo della struttura corrispondano effettivamente alla situazione reale, tanto più se come nella struttura in esame si tratta di una costruzione datata e della quale si hanno poche informazioni circa i dettagli relativi alla costruzione, considerando inoltre che, come già anticipato, sforzi secondari e altri fattori vengono trascurati nella valutazione del fenomeno della fatica. Nel seguito si prenderanno in esame le ipotesi su masse strutturali, rigidezze dei vincoli e momento d’inerzia delle aste di parete, grandezze che caratterizzano in particolare il comportamento dinamico della struttura; per questo sarebbe ancora più difficilmente verificabile se tali ipotesi corrispondano effettivamente alla costruzione reale. Da queste problematiche nasce l’esigenza di affinare il modello numerico agli Elementi Finiti, identificando a posteriori quei parametri meccanici ritenuti significativi per il comportamento dinamico della struttura in esame. In specifico si andrà a porre il problema di identificazione come un problema di ottimizzazione, dove i valori dei parametri meccanici vengono valutati in modo che le caratteristiche dinamiche del modello, siano il più simili possibile ai risultati ottenuti da elaborazioni sperimentali sulla struttura reale. La funzione costo è definita come la distanza tra frequenze proprie e deformate modali ottenute dalla struttura reale e dal modello matematico; questa funzione può presentare più minimi locali, ma la soluzione esatta del problema è rappresentata solo dal minimo globale. Quindi il successo del processo di ottimizzazione dipende proprio dalla definizione della funzione costo e dalla capacità dell’algoritmo di trovare il minimo globale. Per questo motivo è stato preso in considerazione per la risoluzione del problema, l’algoritmo di tipo evolutivo DE (Differential Evolution Algorithm), perché gli algoritmi genetici ed evolutivi vengono segnalati per robustezza ed efficienza, tra i metodi di ricerca globale caratterizzati dall’obiettivo di evitare la convergenza in minimi locali della funzione costo. Obiettivo della tesi infatti è l’utilizzo dell’algoritmo DE modificato con approssimazione quadratica (DE-Q), per affinare il modello numerico e quindi ottenere l’identificazione dei parametri meccanici che influenzano il comportamento dinamico di una struttura reale, il ponte ferroviario metallico a Pontelagoscuro.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Polynomial regression using a perceptron with axo-axonic connections

Social behavior is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks

Combining Legendre's Polynomials and Genetic Algorithm in the Solution of Nonlinear Initial-Value Problems

This work develops a method for solving ordinary differential equations, that is, initial-value problems, with solutions approximated by using Legendre's polynomials. An iterative procedure for the adjustment of the polynomial coefficients is developed, based on the genetic algorithm. This procedure is applied to several examples providing comparisons between its results and the best polynomial fitting when numerical solutions by the traditional Runge-Kutta or Adams methods are available. The resulting algorithm provides reliable solutions even if the numerical solutions are not available, that is, when the mass matrix is singular or the equation produces unstable running processes.

Fast ray-tracing algorithm for circumstellar structures (FRACS) II. Disc parameters of the B[e] supergiant CPD-57 degrees 2874 from VLTI/MIDI data

Context. B[e] supergiants are luminous, massive post-main sequence stars exhibiting non-spherical winds, forbidden lines, and hot dust in a disc-like structure. The physical properties of their rich and complex circumstellar environment (CSE) are not well understood, partly because these CSE cannot be easily resolved at the large distances found for B[e] supergiants (typically greater than or similar to 1 kpc). Aims. From mid-IR spectro-interferometric observations obtained with VLTI/MIDI we seek to resolve and study the CSE of the Galactic B[e] supergiant CPD-57 degrees 2874. Methods. For a physical interpretation of the observables (visibilities and spectrum) we use our ray-tracing radiative transfer code (FRACS), which is optimised for thermal spectro-interferometric observations. Results. Thanks to the short computing time required by FRACS (<10 s per monochromatic model), best-fit parameters and uncertainties for several physical quantities of CPD-57 degrees 2874 were obtained, such as inner dust radius, relative flux contribution of the central source and of the dusty CSE, dust temperature profile, and disc inclination. Conclusions. The analysis of VLTI/MIDI data with FRACS allowed one of the first direct determinations of physical parameters of the dusty CSE of a B[e] supergiant based on interferometric data and using a full model-fitting approach. In a larger context, the study of B[e] supergiants is important for a deeper understanding of the complex structure and evolution of hot, massive stars.

Subspace wavepacket evolution with Newton polynomials

Time-dependent wavepacket evolution techniques demand the action of the propagator, exp(-iHt/(h)over-bar), on a suitable initial wavepacket. When a complex absorbing potential is added to the Hamiltonian for combating unwanted reflection effects, polynomial expansions of the propagator are selected on their ability to cope with non-Hermiticity. An efficient subspace implementation of the Newton polynomial expansion scheme that requires fewer dense matrix-vector multiplications than its grid-based counterpart has been devised. Performance improvements are illustrated with some benchmark one and two-dimensional examples. (C) 2001 Elsevier Science B.V. All rights reserved.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

Modelling of microstructure formation and evolution during solidification

A comprehensive probabilistic model for simulating microstructure formation and evolution during solidification has been developed, based on coupling a Finite Differential Method (FDM) for macroscopic modelling of heat diffusion to a modified Cellular Automaton (mCA) for microscopic modelling of nucleation, growth of microstructures and solute diffusion. The mCA model is similar to Nastac's model for handling solute redistribution in the liquid and solid phases, curvature and growth anisotropy, but differs in the treatment of nucleation and growth. The aim is to improve understanding of the relationship between the solidification conditions and microstructure formation and evolution. A numerical algorithm used for FDM and mCA was developed. At each coarse scale, temperatures at FDM nodes were calculated while nucleation-growth simulation was done at a finer scale, with the temperature at the cell locations being interpolated from those at the coarser volumes. This model takes account of thermal, curvature and solute diffusion effects. Therefore, it can not only simulate microstructures of alloys both on the scale of grain size (macroscopic level) and the dendrite tip length (mesoscopic level), but also investigate nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies. The calculated results are compared with values of grain sizes and solidification morphologies of microstructures obtained from a set of casting experiments of Al-Si alloys in graphite crucibles.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

Dynamical modelling of a genetic algorithm

This work addresses the signal propagation and the fractional-order dynamics during the evolution of a genetic algorithm (GA). In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations during some generations and the corresponding fitness variations are evaluated. Three distinct fitness functions are used to study their influence in the GA dynamics. The input and output signals are studied revealing a fractional-order dynamic evolution, characteristic of a long-term system memory.

Influence of attenuation correction in the MPI image reconstructed by the ‘Evolution for Cardiac’™

The acquisition of a Myocardial Perfusion image (MPI) is of great importance for the diagnosis of the coronary artery disease, since it allows to evaluate which areas of the heart aren’t being properly perfused, in rest and stress situations. This exam is greatly influenced by photon attenuation which creates image artifacts and affects quantification. The acquisition of a Computerized Tomography (CT) image makes it possible to get an atomic images which can be used to perform high-quality attenuation corrections of the radiopharmaceutical distribution, in the MPI image. Studies show that by using hybrid imaging to perform diagnosis of the coronary artery disease, there is an increase on the specificity when evaluating the perfusion of the right coronary artery (RCA). Using an iterative algorithm with a resolution recovery software for the reconstruction, which balances the image quality, the administered activity and the scanning time, we aim to evaluate the influence of attenuation correction on the MPI image and the outcome in perfusion quantification and imaging quality.