Multirate sampled-data yaw-damper and modal suppression system design

A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project

Robust and Reliable Multidiscipline Ship Design

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83553/1/AIAA-2010-9394-777.pd

Uncertainty propagation in multi-agent systems for multidisciplinary optimization problems

International audienceBecause of uncertainties on models and variables, deterministic multidisciplinary optimization may achieve under-sizing (without design margins) or over-sizing (with arbitrary design margins). Thus, it is necessary to implement multidisciplinary optimization methods that take into account the uncertainties in order to design systems that are both robust and reliable. Probabilistic methods such as reliability-based design optimization (RBDO) or robust design methods, provide designers with powerful decision-making tools but may involve very time-consuming calculations. New optimization approaches have been developed to deal with such complex problems. Auto-adaptive Multi-Agent Systems (AMAS) is a new approach developed recently, allowing to take into account the various aspects of a multidisciplinary optimization problem (multi-level, computation burden etc.). This approach was suggested for solving complex deterministic optimization problem. Now, the question of the integration of uncertainties in this multi-agent based optimization arises. The aim of this paper is to propose a new methodology for integrating the treatment of uncertainties in an adaptive multi-agent system for sequential optimization. The developed method employs a single loop process in which cycles of deterministic optimization alternate with evaluations of the system reliability. For each cycle, the optimization and the reliability analysis are decoupled from each other. The reliability analysis is carried out at agent level and only after the resolution of the deterministic optimization, to verify the feasibility of the constraints under uncertainties. Following the probabilistic study, the constraints violated (with low reliability) are shifted to the area of feasibility by integrating adaptive safety coeficients whose calculations are based on the agent-level reliability information. The method developed is applied to a conceptual aircraft design problem

Robust online motion planning with reachable sets

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 51-55).In this thesis we consider the problem of generating motion plans for a nonlinear dynamical system that are guaranteed to succeed despite uncertainty in the environment, parametric model uncertainty, disturbances, and/or errors in state estimation. Furthermore, we consider the case where these plans must be generated online, because constraints such as obstacles in the environment may not be known until they are perceived (with a noisy sensor) at runtime. Previous work on feedback motion planning for nonlinear systems was limited to offline planning due to the computational cost of safety verification. Here we augment the traditional trajectory library approach by designing locally stabilizing controllers for each nominal trajectory in the library and providing guarantees on the resulting closed loop systems. We leverage sums-of-squares programming to design these locally stabilizing controllers by explicitly attempting to minimize the size of the worst case reachable set of the closed-loop system subjected to bounded disturbances and uncertainty. The reachable sets associated with each trajectory in the library can be thought of as "funnels" that the system is guaranteed to remain within. The resulting funnel library is then used to sequentially compose motion plans at runtime while ensuring the safety of the robot. A major advantage of the work presented here is that by explicitly taking into account the effect of uncertainty, the robot can evaluate motion plans based on how vulnerable they are to disturbances. We demonstrate our method on a simulation of a plane flying through a two dimensional forest of polygonal trees with parametric uncertainty and disturbances in the form of a bounded "cross-wind". We further validate our approach by carefully evaluating the guarantees on invariance provided by funnels on two challenging underactuated systems (the "Acrobot" and a small-sized airplane).by Anirudha Majumdar.S.M

Modeling Operational Variability for Robust Multidisciplinary Design Optimization

International audienceThe aim of this paper is to model and propagate operational uncertainties in view of its integration in a multidisciplinary optimization methodology for aircraft robust design. From databases relative to one specic type of long-range airplane, we analyze the variations of four ight parameters (altitude, speed, temperature and range), and build the associated statistical distributions. Then, using an uncertainty propagation methodology, we identify the distribution of operational costs

Probabilistic Fail-Safe Size Optimization of Aerospace Structures Under Several Sources of Uncertainty

Programa Oficial de Doutoramento en Enxeñaría Civil . 5011V01[Abstract] This work presents a research on the probabilistic fail-safe size optimization of aerospace structures. The goal is to design minimum weight structures taking into account possible damage scenarios, as well as several sources of uncertainty. The first type of uncertainty refers to the one present in structural parameters, which can be characterized as aleatory, epistemic or hybrid uncertainty. The second type of uncertainty pertains to the ignorance of what partial collapse will occur in an accidental failure event. The last type of uncertainty is related to debris characterization in the event of an engine failure, due to the randomness in the parameters defining the debris, such as the number of impacts or the location and size of holes in the fuselage. Several methodologies have been developed to deal with the first type of uncertainty: fail-safe Reliability-Based Design Optimization (fail-safe RBDO) using the Sequential Optimization and Reliability Assessment method (SORA), fail-safe Evidence-Based Design Optimization (fail-safe EBDO) using the decoupled EBDO approach, and fail-safe Hybrid Reliability-Based Design Optimization (fail-safe HRBDO) using a fast-convergence decoupled strategy that was developed by the author to deal with random and evidence variables simultaneously. Concerning the second type of uncertainty, two methodologies are proposed in this research to address the probability of occurrence of each damage scenario: the Probability-Damage approach for Fail-Safe Design Optimization (PDFSO) and the Reliability-Index based strategy for the Probability-Damage Approach in Fail-Safe Design Optimization ( -PDFSO) where the latter also considers aleatory uncertainty in random structural parameters. Several application examples have been carried out, including a curved stiffened panel of an aircraft fuselage and the rear section of an aircraft fuselage. The last contribution of this research is the development of a framework (DamageCreator) to automatically generate a large enough set of possible damage scenarios from an aircraft mesh, due to an uncontained engine or propeller blade failure event. The debris parameters, such as number of impacts, impact area, spread angles, hole location, debris orientation, size, and velocity, can be considered as random or deterministic. The tool is applied to a cylindrical barrel structure and to a fuselagewing assembly corresponding to a narrow-body aircraft. The programming codes of the proposed methodologies were fully implemented by the author using Matlab and Python environments, as well as Abaqus and Nastran as finite element solvers.[Resumen] Este trabajo presenta una investigación sobre la optimización de tamaño a prueba de fallos de estructuras aeronáuticas en régimen probabilista. El objetivo es diseñar estructuras de peso mínimo teniendo en cuenta los posibles escenarios de daño, así como varias fuentes de incertidumbre. El primer tipo de incertidumbre se refiere a la presente en parámetros estructurales, que puede caracterizarse como incertidumbre aleatoria, epistémica o híbrida. El segundo tipo de incertidumbre se refiere al desconocimiento de qué colapso parcial se producirá en un evento de fallo accidental. El último tipo de incertidumbre está relacionado con la caracterización de los escombros en caso de fallo del motor, debido a la aleatoriedad en los parámetros que definen los escombros, como el número de impactos o la ubicación y el tamaño de los agujeros en el fuselaje. Se han desarrollado varias metodologías para tratar el primer tipo de incertidumbre: la optimización de diseño basada en la fiabilidad a prueba de fallos (RBDO a prueba de fallos) utilizando el método de optimización secuencial y evaluación de la fiabilidad (SORA), la optimización de diseño basada en la evidencia a prueba de fallos (EBDO a prueba de fallos) utilizando el enfoque EBDO desacoplado, y la optimización de diseño basada en la fiabilidad híbrida a prueba de fallos (HRBDO a prueba de fallos) utilizando una estrategia desacoplada de convergencia rápida que fue desarrollada por la autora para tratar las variables aleatorias y de evidencia simultáneamente. En cuanto al segundo tipo de incertidumbre, en esta investigación se proponen dos metodologías para tratar la probabilidad de ocurrencia de cada escenario de daño: el enfoque de la probabilidaddaño para la optimización de diseño a prueba de fallos (PDFSO) y la estrategia basada en el índice de fiabilidad para el enfoque de la probabilidad-daño en la optimización de diseño a prueba de fallos ( -PDFSO), donde esta última también considera la incertidumbre en los parámetros estructurales aleatorios. Se han llevado a cabo varios ejemplos de aplicación, incluyendo un panel curvo rigidizado del fuselaje de un avión y la sección trasera del fuselaje de un avión. La última contribución de esta investigación es el desarrollo de un enfoque (DamageCreator) para generar automáticamente un conjunto suficientemente amplio de posibles escenarios de daño a partir de la malla de una aeronave, debido a un evento de fallo del motor o a un despendimiento de las palas de la hélice. Los parámetros que definen los escombros, como el número de impactos, el área de impacto, los ángulos de propagación, la ubicación de los agujeros, la orientación, el tamaño y la velocidad de los escombros, pueden considerarse aleatorios o deterministas. La herramienta se aplica a una estructura de barril cilíndrico y a un conjunto fuselaje-ala correspondiente a un avión de fuselaje estrecho. Los códigos de programación de las metodologías propuestas fueron implementados íntegramente por la autora utilizando los entornos Matlab y Python, así como Abaqus y Nastran como solvers de elementos finitos.[Resumo] Este traballo presenta unha investigación sobre a optimización de tamaño a proba de fallos de estruturas aeronáuticas en réxime probabilístico. O obxectivo é deseñar estruturas de peso mínimo tendo en conta os posibles escenarios de dano, así como diversas fontes de incerteza. O primeiro tipo de incerteza refírese á presente nos parámetros estruturais, que poden caracterizarse como incerteza aleatoria, epistémica ou híbrida. O segundo tipo de incerteza refírese ao descoñecemento de que colapso parcial se producirá nun caso de fallo accidental. O último tipo de incerteza está relacionado coa caracterización dos cascallos en caso de fallo do motor, debido á aleatoriedade nos parámetros que definen os cascallos, como o número de impactos ou a localización e tamaño dos buratos da fuselaxe. Desenvolvéronse varias metodoloxías para facer fronte ao primeiro tipo de incerteza: a optimización de deseño baseada na fiabilidade a proba de fallos (RBDO a proba de fallos) empregando o método de optimización secuencial e avaliación da fiabilidade (SORA), a optimización de deseño baseada na evidencia a proba de fallos (EBDO a proba de fallos) empregando o enfoque EBDO desacoplado, e a optimizacion de deseño baseada na fiabilidade híbrida a proba de fallos (HRBDO a proba de fallos) empregando unha estratexia desacoplada de converxencia rápida que foi desenvolvida pola autora para tratar as variables aleatorias e de evidencia simultáneamente. En canto ao segundo tipo de incerteza, esta investigación propón dúas metodoloxías para tratar a probabilidade de aparición de cada escenario de dano: o enfoque da probabilidade-dano para a optimización do deseño a proba de fallos (PDFSO) e a estratexia baseada no índice de fiabilidade para o enfoque da probabilidade-dano na optimización do deseño a proba de fallos ( -PDFSO), onde este último tamén considera a incerteza nos parámetros estruturais aleatorios. Leváronse a cabo varios exemplos de aplicación, incluíndo un panel curvo rixidizado dunha fuselaxe de avión e a sección traseira dunha fuselaxe de avión. A última contribución desta investigación é o desenvolvemento dun enfoque (DamageCreator) para xerar automaticamente un conxunto suficientemente amplo de posibles escenarios de dano a partir da malla dunha aeronave, debido ao fallo do motor ou ao desprendemento das palas da hélice. Os parámetros que definen os cascallos, como o número de impactos, a área de impacto, os ángulos de propagación, a localización dos buracos, a orientación, o tamaño e a velocidade dos cascallos, poden considerarse aleatorios ou deterministas. A ferramenta aplícase a unha estrutura de barril cilíndrica e a un conxunto fuselaxe-ás correspondentes a un avión de corpo estreito. Os códigos de programación das metodoloxías propostas foron totalmente implementados pola autora empregando entornos de Matlab e Python, así como Abaqus e Nastran como solvers de elementos finitos.Funding for this work, including the research stay at Cambridge University, has been possible thanks to the sponsorship of the Galician Government through the grant “axudas de apoio á etapa predoutoral cofinanciadas parcialmente polo programa operativo FSE Galicia 2014-2020” under identification number ED481A-2018/193. I am fully grateful for the supportXunta de Galicia; ED481A-2018/19

Mixed H2/H∞ robust controllers in aircraft control problem

A leading cause of accidents during the landing phase of a flight lies in a considerable altitude loss by an aircraft as a result of the impact of a microburst of wind. One of the significant factors focuses primarily on the need to simultaneously satisfy various requirements regarding conditions of environmental disturbances and a wide range of systemic changes. The paper presents an algorithm for synthesizing an optimal controller that solves the mixed H2/H∞ control problem for the stabilization of aircraft in glide-path landing mode in the presence of uncertainty. Firstly, the principles of multi-criteria optimization are presented, and the mixed H2/H∞ problem is interpreted as the synthesis of a system with optimal quadratic performance, subject to its readiness to operate with the worst disturbance. Then, the ensuing section expounds upon the mathematical depiction of the vertical trajectory of aircraft, duly considering the perturbations imposed by wind phenomena. Subsequently, the effectiveness of mixed H2/H∞ control is confirmed compared to autonomous H2 or H∞ regulators through simulation outcomes acquired from the created system. Optimization based on a hybrid (mixed) criterion allowed combining the strengths of locally optimal systems based only on H2 or H∞ theory

A Multidisciplinary Airplane Research Integrated Library With Applications To Partial Turboelectric Propulsion

International audienc