Measurements, Models, Systems and Design

531 s.

Relaxing Fundamental Assumptions in Iterative Learning Control

Iterative learning control (ILC) is perhaps best decribed as an open loop feedforward control technique where the feedforward signal is learned through repetition of a single task. As the name suggests, given a dynamic system operating on a finite time horizon with the same desired trajectory, ILC aims to iteratively construct the inverse image (or its approximation) of the desired trajectory to improve transient tracking. In the literature, ILC is often interpreted as feedback control in the iteration domain due to the fact that learning controllers use information from past trials to drive the tracking error towards zero. However, despite the significant body of literature and powerful features, ILC is yet to reach widespread adoption by the control community, due to several assumptions that restrict its generality when compared to feedback control. In this dissertation, we relax some of these assumptions, mainly the fundamental invariance assumption, and move from the idea of learning through repetition to two dimensional systems, specifically repetitive processes, that appear in the modeling of engineering applications such as additive manufacturing, and sketch out future research directions for increased practicality: We develop an L1 adaptive feedback control based ILC architecture for increased robustness, fast convergence, and high performance under time varying uncertainties and disturbances. Simulation studies of the behavior of this combined L1-ILC scheme under iteration varying uncertainties lead us to the robust stability analysis of iteration varying systems, where we show that these systems are guaranteed to be stable when the ILC update laws are designed to be robust, which can be done using existing methods from the literature. As a next step to the signal space approach adopted in the analysis of iteration varying systems, we shift the focus of our work to repetitive processes, and show that the exponential stability of a nonlinear repetitive system is equivalent to that of its linearization, and consequently uniform stability of the corresponding state space matrix.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133232/1/altin_1.pd

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Structure-Preserving Model Reduction of Physical Network Systems

This paper considers physical network systems where the energy storage is naturally associated to the nodes of the graph, while the edges of the graph correspond to static couplings. The first sections deal with the linear case, covering examples such as mass-damper and hydraulic systems, which have a structure that is similar to symmetric consensus dynamics. The last section is concerned with a specific class of nonlinear physical network systems; namely detailed-balanced chemical reaction networks governed by mass action kinetics. In both cases, linear and nonlinear, the structure of the dynamics is similar, and is based on a weighted Laplacian matrix, together with an energy function capturing the energy storage at the nodes. We discuss two methods for structure-preserving model reduction. The first one is clustering; aggregating the nodes of the underlying graph to obtain a reduced graph. The second approach is based on neglecting the energy storage at some of the nodes, and subsequently eliminating those nodes (called Kron reduction).</p

Reduction of wave linear repetitive processes to singular Roesser model form

Using the elementary operations algorithm, it is shown that a system matrix describing a wave discrete linear repetitive process can be reduced to that for a 2D singular Roesser model. The transformation linking the original polynomial system matrix with its associated 2D singular Roesser form is input-output equivalence. The nature of the resulting system matrix in singular form and the transformation involved are established

Formaciones imaginarias del diseñador gráfico en el discurso del campo académico.

En este trabajo se describe un proyecto de tesis doctoral en el que se analiza el discurso sobre el diseñador gráfico. Se parte del supuesto de que existe una tricotomía de su perfil: 1) el campo profesional, 2) el campo educativo y, 3) el campo académico. Proponemos que dicha tricotomía permite la identificación de imaginarios sobre el tema, y no solo eso, sino que también aporta elementos que conforman la identidad (Bauman, 2002) de un diseñador gráfico. La pregunta de investigación es ¿Cuál es la identidad discursiva del diseñador gráfico en el campo académico? La investigación descrita es de tipo cualitativo y deductivo; para la construcción la identidad discursiva (Van Dijk, T; 2008) del diseñador gráfico, se toman en cuenta diversas publicaciones: principalmente investigaciones y breves artículos difundidos en comunidades/foros de reflexión y debate en torno a la temática, además de memorias de congresos y libros. En apoyo al desarrollo del proyecto se ha diseñado un Laboratorio de Intervención en el Diseño, cuyos objetivos son impulsar el desarrollo social y cultural de los diseñadores gráficos por medio de la investigación, educación continua, producción y vinculación. En un primer acercamiento a las formaciones imaginarias (Pêcheux, 1978) sobre la identidad del diseñador gráfico se centran en el grado de erudición para la ejecución de su trabajo, en la cultura que demuestran y en la autonomía con la que producen