On-line estimation approaches to fault-tolerant control of uncertain systems

This thesis is concerned with fault estimation in Fault-Tolerant Control (FTC) and as such involves the joint problem of on-line estimation within an adaptive control system. The faults that are considered are significant uncertainties affecting the control variables of the process and their estimates are used in an adaptive control compensation mechanism. The approach taken involves the active FTC, as the faults can be considered as uncertainties affecting the control system. The engineering (application domain) challenges that are addressed are: (1) On-line model-based fault estimation and compensation as an FTC problem, for systems with large but bounded fault magnitudes and for which the faults can be considered as a special form of dynamic uncertainty. (2) Fault-tolerance in the distributed control of uncertain inter-connected systems The thesis also describes how challenge (1) can be used in the distributed control problem of challenge (2). The basic principle adopted throughout the work is that the controller has two components, one involving the nominal control action and the second acting as an adaptive compensation for significant uncertainties and fault effects. The fault effects are a form of uncertainty which is considered too large for the application of passive FTC methods. The thesis considers several approaches to robust control and estimation: augmented state observer (ASO); sliding mode control (SMC); sliding mode fault estimation via Sliding Mode Observer (SMO); linear parameter-varying (LPV) control; two-level distributed control with learning coordination

Summary of Research 1994

The views expressed in this report are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.This report contains 359 summaries of research projects which were carried out under funding of the Naval Postgraduate School Research Program. A list of recent publications is also included which consists of conference presentations and publications, books, contributions to books, published journal papers, and technical reports. The research was conducted in the areas of Aeronautics and Astronautics, Computer Science, Electrical and Computer Engineering, Mathematics, Mechanical Engineering, Meteorology, National Security Affairs, Oceanography, Operations Research, Physics, and Systems Management. This also includes research by the Command, Control and Communications (C3) Academic Group, Electronic Warfare Academic Group, Space Systems Academic Group, and the Undersea Warfare Academic Group

Commande Robuste et Contraintes d'Optimisation

This thesis presents an overview of my research activities carried out since my PhD in 2001. In the first section, description of the projects, my different contributions to robust control applied to the spatial field and underwater robotics, are highlighted. My research project for the coming years is then presented; I propose an original and efficient methodology to compute simple control laws by combining \textit{robust control} and \textit{global optimization}. The second part of this thesis is dedicated to the scientific aspects that will help clarify the proposed research project. As a starting point, Youla parametrization is presented as a tool to \textit{render convex} the control problem, and the subsequent work is used as a foundation to establish specifications based on the constraints related to optimization. This theme has served as a driving thread in illustrating how industrial requirements could lead to a control problem. Parallel to this, the question also arose as to the practical realization of results from these methodologies, that is, how they might be implemented in an embedded system. Ariane 5 launcher control is taken as an example for research on the structured control and validation.Ce mémoire présente un panorama des activités de recherche menées depuis ma thèse de doctorat en 2001. Dans une première partie, à travers la description des projets, sont mises en avant les différentes contributions à la commande robuste appliquée au monde spatial et au monde de la robotique sous-marine. On montre alors comment s'est construit le projet de recherche proposé pour les années à venir. Il s'agit de proposer une méthodologie originale et efficace pour régler des lois de commande simple à implémenter en combinant \textit{commande robuste} et \textit{optimisation globale}. La seconde partie de ce mémoire est consacrée à quelques aspects scientifiques qui aident à comprendre le projet de recherche proposé. On y trouve comme point de départ la paramétrisation de Youla en tant qu'outil pour \textit{convexifier} le problème de commande et les travaux qui en ont découlés pour traduire un cahier des charges en terme de contrainte dans un problème d'optimisation. Cette thématique a été un fil conducteur important pour faire le lien avec la demande industrielle de savoir comment les exigences étaient traduites dans le problème de commande. En parallèle, s'est posée la question de la réalisation pratique des résultats issues de ces méthodologies, c'est-à-dire leur implémentation sur un système embarqué. On prendra comme exemple les activités de recherche sur la structuration de correcteur et leur qualification pour les lois de pilotage des lanceurs Ariane 5

An apparatus for high throughput muscle cell experimentation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2006.MIT Science Library copy: printed in pages versus leaves.Also issued in pages.Includes bibliographical references (leaves 183-197).The cardiac ventricular muscle cell (myocyte) is a key experimental system for exploring the mechanical properties of the diseased and healthy heart. The myocyte experimental model provides a higher level of physiological relevance than molecular or myofibril studies while avoiding problems inherent to multicellular preparations including heterogeneity of cell types and diffusion limited extracellular spaces. Millions of primary myocytes that remain viable for four to six hours can be readily isolated from animal models. However, the mechanical properties of only a few physically loaded myocytes can be explored in this time period using current, bulky and expensive instrumentation. In this thesis, a prototype instrument is described that is modular and inexpensive and could form the basis of an array of devices for probing the mechanical properties of single mammnalian myocytes in parallel. This would greatly increase the throughput of scientific experimentation and could be applied as a high content screening instrument in the pharmaceutical industry providing information at the level of a critical cellular phenotype, myocyte mechanical properties, for drug development and toxicology studies.(cont.) The design, development and experimental verification of the modular instrument are presented here. The mathematical, mechanical and electrical characteristics of the novel force sensor and actuator system, Ho control implementation and data processing methodology are discussed. Finally, the functionality of the instrument is demonstrated by implementing novel methodologies for loading and attaching healthy, single mammalian ventricular myocytes to the force sensor and actuator and measuring their isometric twitch force and passive dynamic stiffness at varied sarcomere lengths.by Michael G. Garcia-Webb.Ph.D

Robust Nonlinear Model Predictive Control using Polynomial Chaos Expansions

The performance of model predictive controllers (MPCs) is largely dependent on the accuracy of the model predictions as compared to the actual plant outputs. Irrespective of the model used, first-principles (FP) or empirical, plant-model mismatch is unavoidable. Consequently, model based controllers must be robust to mismatch between the model predictions and the actual process behavior. Controllers that are not robust may result in poor closed loop response and even instability. Model uncertainty can generally be formulated into two broader forms, parametric uncertainty and unstructured uncertainty. Most of the current robust nonlinear MPC have been based on FP-model where only robustness to bounded disturbances rather than parametric uncertainty has been addressed. Systematically accounting for parametric uncertainty in the robust design has been difficult in FP-models due to varying forms in which uncertain parameters occur in the models. To address parametric uncertainty robustness tests based on Structured Singular Value (SSV) and Linear Matrix Inequalities (LMI) have been proposed previously, however these algorithms tend to be conservative because they consider worst-case scenarios and they are also computationally expensive. For instance the SSV calculation is NP-hard and as a result it is not suitable for fast computations. This provides motivation to work on robust control algorithms addressing both parametric and unstructured uncertainty with fast computation times. To facilitate the design of robust controllers which can be computed fast, empirical models are used in which parametric uncertainty is propagated using Polynomial Chaos Expansion (PCE) of parameters. PCE assists in speeding up the computations by providing an analytical expression for the L^2-norm of model predictions while also eliminating the need to design for the worst-case scenario which results in conservatism. Another way of speeding up computations in MPC algorithms is by grouping subsets of available the inputs and outputs into subsystems and by controlling each of the subsystems by MPC controllers of lower dimensions. This latter approach, referred in the literature as Distributed MPC, has been tackled by different strategies involving different degrees of coordination between subsystems but it has not been studied in terms of robustness to model error. Based on the above considerations the current work investigates different robustness aspects of predictive control algorithms for nonlinear processes with special emphasis on the following three situations, i) a nonlinear predictive control based on a Volterra series model where the uncertain parameters are formulated as PCE’s, ii) The application of a PCE-based approach to control and optimization of bioreactors where the model is based on dynamic flux metabolic models, and iii) A Robust Distributed MPC with a robust estimator that is needed to account for the interactions between sub-systems in distributed control

Six Decades of Flight Research: An Annotated Bibliography of Technical Publications of NASA Dryden Flight Research Center, 1946-2006

Titles, authors, report numbers, and abstracts are given for nearly 2900 unclassified and unrestricted technical reports and papers published from September 1946 to December 2006 by the NASA Dryden Flight Research Center and its predecessor organizations. These technical reports and papers describe and give the results of 60 years of flight research performed by the NACA and NASA, from the X-1 and other early X-airplanes, to the X-15, Space Shuttle, X-29 Forward Swept Wing, X-31, and X-43 aircraft. Some of the other research airplanes tested were the D-558, phase 1 and 2; M-2, HL-10 and X-24 lifting bodies; Digital Fly-By-Wire and Supercritical Wing F-8; XB-70; YF-12; AFTI F-111 TACT and MAW; F-15 HiDEC; F-18 High Alpha Research Vehicle, F-18 Systems Research Aircraft and the NASA Landing Systems Research aircraft. The citations of reports and papers are listed in chronological order, with author and aircraft indices. In addition, in the appendices, citations of 270 contractor reports, more than 200 UCLA Flight System Research Center reports, nearly 200 Tech Briefs, 30 Dryden Historical Publications, and over 30 videotapes are included