No / A dynamic system with memory is a system for which knowledge of the equations of motion, together with the state at a given time instant t0 is insufficient to predict the evolution of the state at time instants t>t0. To calculate the response of systems with memory starting from an initial time instant t0, complete knowledge of the history of the system for t<t0 is needed. This is because the state vector does not contain all the information necessary to fully characterize the state of the system, i.e., the state vector of the system is not complete. In this paper, a state space formulation of viscoelastic systems with memory is proposed, which overcomes the concept of memory by enlarging the state vector with a number of internal variables that bear the information about the previous history of the system. The number of these additional internal variables is in some cases finite, in other cases, it would need to be infinite, and an approximated model has to be used with a finite number of internal variables. First a state space representation of the generalized Maxwell model is shown, then a new state space model is presented in which the relaxation function is approximated with Laguerre polynomials. The accuracy of the two models is shown through numerical examples.

No description available.

Problems of cascade connections (synthesis) and decomposition (analysis) are analyzed for two classes of linear systems with infinite dimensional state spaces, namely, 1) admissible systems in the sense of Bart, Gohberg and Kaashoek and 2) regular systems as recently introduced by Weiss. For the class of BGK-admissible systems, it is shown that the product of two admissible systems is again admissible and that a Wiener-Hopf factorization problem can be solved just as in the finite-dimensional case. For the class of regular systems, it is shown that the cascade connection of a rational stable and antistable system has an additive stable-antistable decomposition; this involves giving a distribution interpretation to the solution of a linear Sylvester equation involving unbounded operator coefficients. As an application, some preliminary work is presented toward obtaining a state space solution of the sensitivity minimization problem for a pure delay plant. / Ph. D.

In order to predict the linear stability of combustion systems in industrial-scale gas turbines, a stability analysis was completed using models generated for each of the major dynamic components. Changes in the combustion process of gas turbines to reduce emissions has resulted in large amplitude pressure oscillations associated with a coupling between the natural acoustic modes of the combustor and the unsteady heat release from the flame. Detailed models of the acoustics and the heat release processes were created and assembled, with a time delay element and the appropriate scaling, into a system block diagram to investigate the stability of the system using linear system theory. Wherever possible the analytical models were validated with experimental data. The main goal of this work was to create a design methodology which could be used by industry to predict where instabilities were likely to occur during the design phase. Results show that the system based stability analysis can predict some of the instability frequencies seen in the experimental data, but more refined models are needed to predict every instability. Future work will involve designing experiments to validate and refine the dynamic models already developed. / Master of Science

Disputats, Göteborgs universitet, 2008. / Med litteraturhenvisninger.

Markov jump linear systems find application in many areas including economics, fault-tolerant control, and networked control. Despite significant attention paid to Markov jump linear systems in the literature, few authors have investigated Markov jump linear systems with time-inhomogeneous Markov chains (Markov chains with time-varying transition probabilities), and even fewer authors have considered time-inhomogeneous Markov chains with a priori unknown transition probabilities. This dissertation provides a formal stability and disturbance attenuation analysis for a Markov jump linear system where the underlying Markov chain is characterized by an a priori unknown sequence of transition probability matrices that assumes one of finitely-many values at each time instant. Necessary and sufficient conditions for uniform stochastic stability and uniform stochastic disturbance attenuation are reported. In both cases, conditions are expressed as a set of finite-dimensional linear matrix inequalities (LMIs) that can be solved efficiently. These finite-dimensional LMI analysis results lead to nonconservative LMI formulations for optimal controller synthesis with respect to disturbance attenuation. As a special case, the analysis also applies to a Markov jump linear system with known transition probabilities that vary in a finite set. / Ph. D.

Doctor of Philosophy / Electrical and Computer Engineering / Steven Warren / Linear Systems (a.k.a., Signals and Systems) is an important class in an Electrical Engineering curriculum. A clear understanding of the topics in this course relies on a well-developed notion of lower-level mathematical constructs and procedures, including the roles these procedures play in system analysis. Students with an inadequate math foundation regularly struggle in this class, as they are typically able to perform sequences of the underlying calculations but cannot piece together the higher-level, conceptual relationships that drive these procedures. This dissertation describes an investigation to assess and improve students’ higher-level understanding of Linear Systems concepts. The focus is on the topics of (a) time-domain, linear time-invariant (LTI) system response visualization and (b) Fourier series conceptual understanding, including trigonometric Fourier series (TFS), compact trigonometric Fourier series (CTFS), and exponential Fourier series (EFS). Support data, including exam and online homework data, were collected since 2004 from students enrolled in ECE 512 - Linear Systems at Kansas State University. To assist with LTI response visualization, two online homework modules, Zero Input Response and Unit Impulse Response, were updated with enhanced plots of signal responses and placed in use starting with the Fall 2009 semester. To identify students’ conceptual weaknesses related to Fourier series and to help them achieve a better understanding of Fourier series concepts, teaching-learning interviews were applied between Spring 2010 and Fall 2012. A new concept-based online homework module was also introduced in Spring 2011. Selected final exam problems from 2007 to 2012 were analyzed, and these data were supplemented with detailed mid-term and final exam data from 77 students enrolled in the Spring 2010 and Spring 2011 semesters. In order to address these conceptual learning issues, two frameworks were applied: Bloom’s Taxonomy and APOS theory. The teaching-learning interviews and online module updates appeared to be effective treatments in terms of increasing students’ higher-level understanding. Scores on both conceptual exam questions and more traditional Fourier series exam questions were improved relative to scores received by students that did not receive those treatments.

Σκοπός της παρούσας διπλωματικής εργασίας με τίτλο «Εκπαιδευτικό -Υπολογιστικό Πακέτο για Αριθμητική Επίλυση μη Γραμμικών Εξισώσεων, μη Γραμμικών και Γραμμικών συστημάτων και του Προβλήματος της Βελτιστοποίησης», είναι η δημιουργία ενός υπολογιστικού πακέτου για σημαντικά επιλεγμένα θέματα αριθμητικής ανάλυσης, αξιοποιώντας το προγραμματιστικό περιβάλλον της Matlab. Με δεδομένη την ύπαρξη οργανωμένου εργαστηρίου στο Tμήμα Μαθηματικών του Πανεπιστημίου Πατρών και την εύκολη πρόσβαση των φοιτητών σε αυτό, η δημιουργία ενός τέτοιου υπολογιστικού πακέτου θα μπορούσε άμεσα να αξιοποιηθεί από προπτυχιακούς φοιτητές έτσι ώστε: • να αποτελέσει για κάθε φοιτητή ένα συμπληρωματικό εργαλείο, εύκολα προσβάσιμο ακόμα και έξω από την αίθουσα διδασκαλίας, για την ενίσχυση της κατανόησης εννοιών και μεθόδων που δουλεύονται κατά τη διάρκεια της διδασκαλίας, σε χρόνο που θα επιλέξει και με την επανάληψη που επιθυμεί. • να συνδέσει ο φοιτητής τη θεωρία με δικά του παραδείγματα και με άμεσα αποτελέσματα αξιοποιώντας τα υποδείγματα και το βοηθητικό - φιλικό περιβάλλον που έχουμε δημιουργήσει για την υλοποίηση των επιλεγμένων θεμάτων. • να αποτελέσει το κίνητρο για εξάσκηση στον προγραμματισμό μέσω της Matlab, η οποία δεν διδάσκεται και χρησιμοποιείται μόνο προαιρετικά σε επίπεδο εργασιών. / The aim of this work entitled “Educational Software Package for Numerical Solution of Nonlinear Equations, Nonlinear and Linear Systems and for Optimization Problem” is the creation of a software package which could deal with important issues of the field of mathematics called numerical analysis. This is achieved by using the Matlab computational environment. Taking into account the fact that there is a well equipped lab and easily accessible from students, in the Department of Mathematics of the University of Patras, the presented software package could be used by undergraduates students in order to: • be used by each student as a supplemental “tool” which can be easily accessible, even outside the classroom, for the better understanding of meanings and methods which are introduced during of courses, in time that each student may be selected. • combine theory with his examples and have direct results just by using the “models” of the friendly- assistant environment for the specified issues that are analyzed below. • be the motive for exercising the Matlab environment which could be a useful tool for solving many mathematical, and not only, issues.

Polarimetric systems design has seen recent utilization of linear systems theory for system descriptions. Although noise optimal systems have been shown, bandwidth performance has not been addressed in depth generally and is particularly lacking for Mueller matrix (active) polarimetric systems. Bandwidth must be considered in a systematic way for remote sensing polarimetric systems design. The systematic approach facilitates both understanding of fundamental constraints and design of higher bandwidth polarimetric systems. Fundamental bandwidth constraints result in production of polarimetric "artifacts" due to channel crosstalk upon Mueller matrix reconstruction. This dissertation analyzes bandwidth trade-offs in spatio-temporal channeled Mueller matrix polarimetric systems. Bandwidth is directly related to the geometric positioning of channels in the Fourier (channel) space, however channel positioning for polarimetric systems is constrained both physically and by design parameters like domain separability. We present the physical channel constraints and the constraints imposed when the carriers are separable between space and time. Polarimetric systems are also constrained by noise performance, and there is a trade-off between noise performance and bandwidth. I develop cost functions which account for the trade-off between noise and bandwidth for spatio-temporal polarimetric systems. The cost functions allow a systems designer to jointly optimize systems with good bandwidth and noise performance. Optimization is implemented for a candidate spatio-temporal system design, and high temporal bandwidth systems resulting from the optimization are presented. Systematic errors which impact the bandwidth performance and mitigation strategies for these systematic errors are also presented. Finally, a portable imaging Mueller matrix system is built and analyzed based on the theoretical bandwidth analysis and system bandwidth optimization. Temporal bandwidth performance is improved by 300% over a conventional dual rotating retarder Mueller matrix polarimeter. Reconstruction results from the physical instrument are presented, and issues with the implemented system design are discussed.

By considering Krylov subspace methods in nonstandard inner products, we develop in this thesis new methods for solving large sparse linear systems and examine the effectiveness of existing preconditioners. We focus on saddle point systems and systems with a nonsymmetric, diagonalizable coefficient matrix. For symmetric saddle point systems, we present a preconditioner that renders the preconditioned saddle point matrix nonsymmetric but self-adjoint with respect to an inner product and for which scaling is not required to apply a short-term recurrence method. The robustness and effectiveness of this preconditioner, when applied to a number of test problems, is demonstrated. We additionally utilize combination preconditioning (Stoll and Wathen. SIAM J. Matrix Anal. Appl. 2008; 30:582-608) to develop three new combination preconditioners. One of these is formed from two preconditioners for which only a MINRES-type method can be applied, and yet a conjugate-gradient type method can be applied to the combination preconditioned system. Numerical experiments show that application of these preconditioners can result in faster convergence. When the coefficient matrix is diagonalizable, but potentially nonsymmetric, we present conditions under which the pseudospectra of a preconditioner and coefficient matrix are identical and characterize the pseudospectra when this condition is not exactly fulfilled. We show that when the preconditioner and coefficient matrix are self-adjoint with respect to nearby symmetric bilinear forms the convergence of a particular minimum residual method is bounded by a term that depends on the spectrum of the preconditioned coefficient matrix and a constant that is small when the symmetric bilinear forms are close. An iteration-dependent bound for GMRES in the Euclidean inner product is presented that shows precisely why a standard bound can be pessimistic. We observe that for certain problems known, effective preconditioners are either self-adjoint with respect to the same symmetric bilinear form as the coefficient matrix or one that is nearby.