Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-01-11T17:29:03Z No. of bitstreams: 1 exuperrybarroscosta.pdf: 14654639 bytes, checksum: f25579d82da6242e77a04745322538ad (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-01-23T13:44:17Z (GMT) No. of bitstreams: 1 exuperrybarroscosta.pdf: 14654639 bytes, checksum: f25579d82da6242e77a04745322538ad (MD5) / Made available in DSpace on 2018-01-23T13:44:17Z (GMT). No. of bitstreams: 1 exuperrybarroscosta.pdf: 14654639 bytes, checksum: f25579d82da6242e77a04745322538ad (MD5) Previous issue date: 2017-09-15 / O presente trabalho propõe uma nova metodologia de Geração de Sinal Sub-Ótimo de Excitação e Estimação Ótima de Parâmetros de sistemas não lineares. É proposto que a avaliação de cada sinal deva considerar, entre outros fatores, a diferença entre os parâmetros reais da planta e os obtidos pela estimação. Entretanto esta métrica não é trivial de ser obtida uma vez que os valores reais são desconhecidos. Para tanto é adotada a hipótese de que, se um sistema real puder ser razoavelmente aproximado por uma caixa branca, é possível utilizar este modelo como referência para indicar o impacto de um sinal sobre a estimação paramétrica. Desta forma, é utilizada uma metodologia de otimização dividida em dois níveis: (i) Nível Interno; para um dado sinal de excitação um método de otimização não linear busca o conjunto ótimo de parâmetros que minimiza o erro entre os sinais de saída do modelos original e do de referência. (ii) No nível externo um método de otimização baseado em meta-heurística é responsável por encontrar o melhor sinal de excitação com base na função custo composta de uma soma ponderada de métricas que consideram o erro entre os sinais de saída do modelo otimizado e do de referência, a diferença quadrática entre seus parâmetros, e o custo em relação ao tempo e espaço necessários para executar o experimento. Portanto, a aplicação da metodologia proposta vem suprir a necessidade de estimar sistemas não lineares apropriadamente, encontrando um conjunto de parâmetros capaz de generalizar o comportamento do sistema real, através de um sinal de excitação que cumpra requisitos práticos do processo. A eficácia da metodologia proposta é analisada em detalhes através de resultados obtidos utilizando sistemas de fluídos, sistemas caóticos e de robótica móvel, tanto sobre rodas quanto subaquática. / The present work proposes a novel methodology for Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation of nonlinear systems. It is proposed that the evaluation of each signal must to take into account, among other factors, the difference between real system parameters and the obtained by estimation. However, this metric is not trivially obtained once the real parameters values are unknown. To do so it is adopted the hypothesis that, if the system can be fairly approximate by a white box model, it is possible to use this model as a benchmark to indicate the impact of a signal on a parametric estimation. In this way, the method uses an optimization methodology divided into two levels: (i) Inner Level; For a given excitation signal a nonlinear optimization method searches for the optimal set of parameters that minimizes the error between the output signals of the original and the benchmark models. (ii) At the outer level, an optimization method based on metaheuristics is responsible for finding the best excitation signal, based on the cost function composed of a weighted sum of metrics, that considers the error between the output signals of the optimized model and the benchmark, the quadratic difference between its parameters, and the cost in relation to the time and space required to execute the experiment. Thus, the application of the proposed methodology comes to supply the need to estimate nonlinear systems appropriately, finding a set of parameters capable of generalizing the behavior of the real system, through an excitation signal that fulfills practical requirements of the process. The proposed methodology is analyzed in detail through results obtained using fluid systems, chaotic systems and mobile robotics, both wheeled and underwater.

Lee Fu Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 96-104). / Abstract --- p.i / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- The contribution of this project --- p.3 / Chapter 1.3 --- Scope of Thesis --- p.3 / Chapter 2. --- Background Study --- p.4 / Chapter 2.1 --- Related works of General DBMS User Interface --- p.4 / Chapter 2.1.1 --- Linear System --- p.4 / Chapter 2.1.2 --- Form-Based System --- p.6 / Chapter 2.1.3 --- Other Approaches --- p.8 / Chapter 2.2 --- Related works of Chinese System --- p.9 / Chapter 2.2.1 --- Artificial Natural Language --- p.9 / Chapter 2.2.2 --- """Chinesized"" English Database Query Language" --- p.9 / Chapter 2.2.3 --- Chiq1 --- p.10 / Chapter 3. --- Design Principles --- p.11 / Chapter 3.1 --- Data Model --- p.11 / Chapter 3.2 --- Language Naturalness --- p.11 / Chapter 3.3 --- Novice Users vs Expert Users --- p.12 / Chapter 3.4 --- Practical Requirements --- p.14 / Chapter 3.4.1 --- Relational Algebra Operators --- p.15 / Chapter 3.4.2 --- Divide and Conquer Querying Strategy --- p.16 / Chapter 3.4.3 --- Unit of Operations --- p.17 / Chapter 3.4.4 --- Graphical User Interface (GUI) --- p.18 / Chapter 3.4.5 --- Direct Object Manipulation --- p.19 / Chapter 3.5 --- SQL Expressiveness --- p.19 / Chapter 4. --- Query Specification in Chinese --- p.21 / Chapter 4.1 --- Defining Elementary Operations --- p.21 / Chapter 5. --- Implementation of the System Design --- p.29 / Chapter 5.1 --- Hardware and Software Configuration --- p.29 / Chapter 5.1.1 --- Basic Components --- p.29 / Chapter 5.1.2 --- Procedures for Data Retrieval --- p.30 / Chapter 5.2 --- System Design --- p.32 / Chapter 5.2.1 --- Common Operations --- p.32 / Chapter 5.2.2 --- Select the Required Tables --- p.33 / Chapter 5.2.3 --- Performing Join --- p.35 / Chapter 5.2.4 --- Performing Restriction --- p.36 / Chapter 5.2.5 --- Performing Projection --- p.37 / Chapter 5.2.6 --- Completion of Query --- p.38 / Chapter 5.2.7 --- Other Basic Operations --- p.39 / Chapter 5.2.8 --- Set Operations --- p.40 / Chapter 5.2.9 --- Composing and Decomposing a Complex Query --- p.41 / Chapter 6. --- Query Formulation in the Interface --- p.42 / Chapter 6.1 --- Example 1 (Simple Query - Novice User) --- p.45 / Chapter 6.2 --- Example 2 (Simple Query - Expert User) --- p.65 / Chapter 6.3 --- Example 3 (Simple Query with Group-By Feature) --- p.77 / Chapter 6.4 --- Example 4 (Complex Query with Set Operations) --- p.87 / Chapter 7. --- Summary and Conclusions --- p.90 / Chapter 7.1 --- Summary of Accomplishment --- p.90 / Chapter 7.2 --- Future Work --- p.94 / Chapter 7.3 --- Conclusion --- p.95 / Chapter 8. --- References --- p.96 / Chapter 9. --- Appendix A : 66 Testing Queries --- p.105 / Chapter 10. --- Appendix B : Glossary --- p.112 / Chapter 11. --- Appendix C : Programs Listing --- p.115

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Seyyed Jamaaloddin Golestaani. / Ph.D.

Aerodynamic parameter estimation from closed loop data has been developed as another research area since control and stability augmentation systems have been mandatory for aircrafts. This thesis focuses on aerodynamic parameter estimation of an air to ground missile from closed loop data using separate surface excitations. A design procedure is proposed for designing separate surface excitations. The effect of excitations signals to the system is also analyzed by examining autopilot disturbance rejection performance. Aerodynamic parameters are estimated using two different estimation techniques which are ordinary least squares and complex linear regression. The results are compared with each other and with the aerodynamic database. An application of the studied techniques to a real system is also given to validate that they are directly applicable to real life.

Aerodynamic parameter estimation from closed loop data has been developed as another research area since control and stability augmentation systems have been mandatory for aircrafts. This thesis focuses on aerodynamic parameter estimation of an air to ground missile from closed loop data using separate surface excitations. A design procedure is proposed for designing separate surface excitations. The effect of excitations signals to the system is also analyzed by examining autopilot disturbance rejection performance. Aerodynamic parameters are estimated using two different estimation techniques which are ordinary least squares and complex linear regression. The results are compared with each other and with the aerodynamic database. An application of the studied techniques to a real system is also given to validate that they are directly applicable to real life.

This thesis reports the identification of linear and nonlinear handling models for road vehicles starting from structural identifiability analysis, continuing with the experiments to acquire data on a vehicle equipped with a sensor set and data acquisition system and ending with the estimation of parameters using the collected data. The 2 degrees of freedom (dof) linear model structure originates from the well known linear bicycle model that is frequently used in handling analysis of road vehicles. Physical parameters of the bicycle model structure are selected as the unknown parameter set that is to be identified. Global identifiability of the model structure is analysed, in detail, and concluded according to various available sensor sets. Physical parameters of the bicycle model structure are estimated using prediction error estimation method. Genetic algorithms are used in the optimization phase of the identification algorithm to overcome the difficulty in the selection of initial values for parameter estimates. Validation analysis of the identified model is also presented. Identified model is shown to track the system response successfully. Following the linear model identification, identification of 3 dof nonlinear models are studied. Local identifiability analysis is done and optimal input is designed using the same procedure for linear model structure identification. Practical identifiability analysis is performed using Fisher Information Matrix. Physical parameters are estimated using the data from simulated experiments. High accuracy estimates are obtained. Methodology for nonlinear handling model identification is presented.

L'objectif principal de ce travail a été d'apporter une nouvelle contribution quant à l'approche de contrôle optimal pendant la phase d'identification. Il s'agissait de trouver la commande à appliquer pendant l'expérience qui permet d'optimiser un critère qui est fonction des sensibilités des sorties par rapport aux paramètres du modèle à identifier. Cette approche couplant contrôleur prédictif sous contraintes et estimateur a résolu en ligne le problème d'identification à chaque instant en utilisant l'observateur. En ce sens, c'est une approche permettant d'automatiser et d'optimiser le design d'expérience, tout en réalisant conjointement l'identification d'un paramètre du modèle spécifié. L'aspect temps réel a été pris en compte dans la formulation de la solution apportée. Dans ce contexte, nous avons introduit deux stratégies de commande pour l'identification optimale. La première était basée sur un modèle de prédiction non linéaire et la seconde sur un modèle linéaire temps variant. Si le temps devient un paramètre critique pour l'implémentation de l'approche, cette dernière vise à réduire le temps alloué à l'optimisation. L'approche d'identification optimale en ligne a été appliquée à deux problèmes concrets du Génie des Procédés (réaction de saponification et cuisson de peintures). Ces exemples ont permis de vérifier en simulation, l'efficacité et la faisabilité de cette approche. / The main aim of this work is to give a new approach of optimal control during the phase of identification. The question is how to tune the control action to be applied during the experiment optimize a criterion which is function of the sensitivities of the mesure with respect to the parameters of the model to be identified. This approach coupling constrained predictive controller and estimator solves on line the problem of identification by using the observer. In that sense, it is an approach allowing an optimal and automatic design of experiment, while performing at the same time the identification of one parameter of the specified model. The real time aspect was taken into account in the formulation of the solution. In this context, we introduced two strategies for optimal identification : the first one is based on a nonlinear model of prediction and the second one is based on a linear time varying model that may be used if the real time aspect becomes a critical parameter for the implementation of the approach. This approach of on line optimal identification was applied on two concrete problems in Chemical Engineering. These examples show the performance and the feasibility of this approach.

Dans ce travail de thèse, nous nous focalisons sur le problème de l'intégration d'incertitude à erreurs bornées pour les systèmes dynamiques, dont les entrées et les états initiaux doivent être optimaux afin de réaliser certaines fonctionnalités.Le document comporte 5 chapitres: le premier est une introduction présentant le panorama du travail. Le deuxième chapitre présente les outils de base de l'analyse par intervalle. Le chapitre 3 est dédié à l'estimation d'états et de paramètres. Nous décrivons d'abord une procédure pour résoudre un système d'équations différentielles ordinaires avec l'aide de cet outil. Ainsi, une estimation des états à partir des conditions initiales peut être faite. Les systèmes différentiels considérés dépendent de paramètres qui doivent être estimés. Ce problème inverse pourra être résolu via l'inversion ensembliste. L'approche par intervalle est une procédure déterministe naturelle sans incertitude, tous les résultats obtenus sont garantis. Néanmoins, cette approche n'est pas toujours efficace, ceci est dû au fait que certaines opérations ensemblistes conduisent à des temps de calcul important. Nous présentons quelques techniques, par cela, nous nous plaçons dans un contexte à erreurs bornées permettant d'accélérer cette procédure. Celles-ci utilisent des contracteurs ciblés qui permettent ainsi une réduction de ce temps. Ces algorithmes ont été testés et ont montré leur efficacité sur plusieurs applications: des modèles pharmacocinétiques et un modèle du vol longitudinal d'avion en atmosphère au repos.Le chapitre 4 présente la recherche d'entrées optimales dans le cadre analyse par intervalle, ce qui est une approche originale. Nous avons construit plusieurs critères nouveaux permettant cette recherche. Certains sont intuitifs, d'autres ont nécessité un développement théorique. Ces critères ont été utilisés pour la recherche d'états initiaux optimaux. Des comparaisons ont été faites sur plusieurs applications et l'efficacité de certains critères a été mise en évidence.Dans le chapitre 5, nous appliquons les approches présentées précédemment au diagnostic via l'estimation de paramètres. Nous avons développé un processus complet pour le diagnostic et aussi formulé un processus pour le diagnostic actif avec une application en aéronautique. Le dernier chapitre résume les travaux réalisés dans cette thèse et essaye de donner des perspectives à la recherche.Les algorithmes proposés dans ce travail ont été développés en C++ et utilisent l'environnement du calcul ensembliste. / In this work, we will study the uncertainty integration problem in a bounded error context for the dynamic systems, whose input and the initial state have to be optimized so that some other operation could be more easily and better obtained. This work is consisted of 6 chapters : the chapter 1 is an introduction to the general subject which we will discuss about. The chapter 2 represents the basic tools of interval analysis.The chapter 3 is dedicated to state estimation and parameter estimation. We explain at the first, how to solve the ordinary differential equation using interval analysis, which will be the basic tool for the state estimation problem given the initial condition of studied systems. On the other ride, we will look into the parameter estimation problem using interval analysis too. Based on a simple hypothesis over the uncertain variable, we calculate the system's parameter in a bounded error form, considering the operation of intervals as the operation of sets. Guaranteed results are the advantage of interval analysis, but the big time consumption is still a problem for its popularization in many non linear estimation field. We present our founding techniques to accelerate this time consuming processes, which are called contractor in constraint propagation field. At the end of this chapter, différent examples will be the test proof for our proposed methods.Chapter 4 presents the searching for optimal input in the context of interval analysis, which is an original approach. We have constructed several new criteria allow such searching. Some of them are intuitive, the other need a theoretical proof. These criteria have been used for the search of optimal initial States and le better parameter estimation results. The comparisons are done by using multiple applications and the efficiency is proved by evidence.In chapter 5, we applied the approaches proposed above in diagnosis by state estimation and parameter estimation. We have developed a complete procedure for the diagnosis. The optimal input design has been reconsidered in an active diagnosis context. Both state and parameter estimation are implemented using an aeronautical application in literature.The last chapter given a brief summary over the realized subject, some further research directions are given in the perspective section.All the algorithms are written in C/C++ on a Linux based operation system.