Direct lift control for aircraft has been around in the aeronautical industry for decades but is mainly used in commercial aircraft with dedicated direct lift control surfaces. The focus of this thesis is to investigate if direct lift control is feasible for a fighter aircraft, similar to Saab JAS 39 Gripen, without dedicated control surfaces. The modelled system is an aircraft that is inherently unstable and contains nonlinearities both in its aerodynamics and in the form of limited control surface deflection and deflection rates. The dynamics of the aircraft are linearised around a flight case representative of a landing scenario. Direct lift control is then applied to give a more immediate relation from pilot stick input to change in flight path angle while also preserving the pitch attitude. Two different control strategies, linear quadratic control and model predictive control, were chosen for the implementation. Since fighter aircraft are systems with fast dynamics it was important to limit the computational time. This constraint motivated the use of specialised methods to speed up the optimisation of the model predictive controller. Results from simulations in a nonlinear simulation environment supplied by Saab, as well as tests in high-fidelity flight simulation rigs with a pilot, proved that direct lift control is feasible for the investigated fighter aircraft. Sufficient control authority and performance when controlling the flight path angle were observed. Both developed controllers have their own advantages and which strategy is the most suitable depends on what the user prioritises. Pilot workload during landing as well as precision at touch down were deemed similar to conventional control.

"Maintaining an efficient and reliable infrastructure requires continuous monitoring and control. In order to accomplish these tasks, algorithms are needed to process large sets of data and for modeling based on these processed data sets. For this reason, computationally efficient and accurate modeling algorithms along with data compression techniques and optimal yet practical control methods are in demand. These tools can help model structures and improve their performance. In this thesis, these two aspects are addressed separately. A principal component analysis based adaptive neuro-fuzzy inference system is proposed for fast and accurate modeling of time-dependent behavior of a structure integrated with a smart damper. Since a smart damper can only dissipate energy from structures, a challenge is to evaluate the dissipativity of optimal control methods for smart dampers to decide if the optimal controller can be realized using the smart damper. Therefore, a generalized deterministic definition for dissipativity is proposed and a commonly used controller, LQR is proved to be dissipative. Examples are provided to illustrate the effectiveness of the proposed modeling algorithm and evaluating the dissipativity of LQR control method. These examples illustrate the effectiveness of the proposed modeling algorithm and dissipativity of LQR controller."

Orientador: Gilberto Pechoto de Melo / Resumo: As metodologias de monitoramento da integridade estrutural baseadas em observadores de estado, em sua grande maioria, utilizam o resíduo obtido a partir da diferença entre a medida e a estimativa de dada resposta dinâmica do sistema para o processo de detecção de danos. Contudo, em determinadas situações, tem-se interesse em realizar o monitoramento através de certa resposta dinâmica que não pode ser medida diretamente. Desta forma, a principal contribuição deste trabalho é propor uma metodologia de detecção de danos para sistemas mecânicos, cujo resíduo é obtido a partir da diferença entre as estimativas do comportamento dinâmico de determinada região do sistema. Estas estimativas são geradas por dois observadores de estado de ordem plena em paralelo, ambos projetados a partir do modelo físico-matemático do sistema em monitoramento sem danos, cujos os ganhos ótimos são determinados pelo método LQR, do inglês Linear Quadratic Regulator. A diferença entre os observadores consiste em serem baseados em conjuntos de medidas distintos. Simulações computacionais são apresentadas para demonstrar a aplicação desta metodologia, de maneira que são discutidas as vantagens e desvantagens em monitorar o sistema utilizando diferentes tipos de força de excitação. Os resultados obtidos são satisfatórios para a detecção dos tipos de dano considerados neste trabalho. / Abstract: Structural health monitoring methodologies based on state observers, for the most part, use the residual obtained from the di erence between the measurement and the estimate of the given dynamic response of the system to the damage detection process. However, in certain situations, it is interesting to carry out the monitoring through a certain dynamic response that can not be measured directly. In this way, the main contribution of this work is to propose a methodology of damage detection for mechanical systems, whose residue is obtained from the di erence between the estimates of the dynamic behavior of a certain region of the system. These estimates are generated by two parallel full-order state observers, both designed from the physical-mathematical model of the monitoring system without damages, whose optimal gains are determined by the LQR (Linear Quadratic Regulator) method. The di erence between observers is that they are based on di erent sets of measures. Computational simulations are presented to demonstrate the application of this methodology, so that the advantages and disadvantages of monitoring the system using di erent types of excitation force are discussed. The results obtained are satisfactory for the detection of the types of damage considered in this work. / Mestre

L'objectif de cette thèse est d'optimiser l'utilisation d'actionneurs redondants pour un avion de transport lorsqu’une défaillance des actionneurs arrive en vol. La tolérance aux pannes résulte ici de la redondance des actionneurs présents sur l’avion. Différents concepts et méthodes classiques liés aux chaînes de commande de vol tolérantes aux pannes sont d'abord examinés et de nouveaux concepts utiles pour l'analyse requise sont introduits. Le problème qui est abordé ici est de développer une méthode de gestion des pannes des commandes de vol dans le cas d'une défaillance partielle des actionneurs, qui va permettre à l'avion de poursuivre en toute sécurité la manœuvre prévue. Une approche de commande en deux étapes est proposée et appliquée à la fois à l'évaluation de la manoeuvrabilité restante et à la conception de structures de commande tolérante aux pannes. Dans le premier cas, une méthode d'évaluation hors ligne des qualités de vol basée sur la commande prédictive est proposée. Dans le second cas, une structure de commande tolérante aux pannes basée sur la commande non linéaire inverse et la réaffectation des actionneurs en ligne est développée. Dans les deux cas, un problème de programmation linéaire quadratique (LQ) est formulé. Différents cas de pannes sont considérés lorsqu'un avion effectue une manoeuvre classique. Trois solveurs numériques sont appliqués aux solutions en ligne et hors ligne des problèmes LQ qui en résultent. / The objective of this thesis is to optimize the use of redundant actuators for a transportation aircraft once some actuators failure occurs during the flight. Here, the fault tolerant ability resulting from the redundant actuators is mainly considered. Different classical concepts and methods related to a fault tolerant flight control channel are first reviewed and new concepts useful for the required analysis are introduced. The problem which is tackled here is to develop a design methodology for fault tolerant flight control in the case of a partial actuator failure which will allow the aircraft to continue safely the intended maneuver. A two stages control approach is proposed and applied to both the remaining maneuverability evaluation and a fault tolerant control structure design. In the first case, an offline handling qualities assessment method based on Model Predictive Control is proposed. In the second case, a fault tolerant control structure based on Nonlinear Inverse Control and online actuator reassignment is developed. In both cases, a Linear Quadratic (LQ) programming problem is formulated and different failure cases are considered when an aircraft performs a classical maneuver. Three numerical solvers are studied and applied to the offline and online solutions of the resulting LQ problems.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-22T13:19:28Z No. of bitstreams: 1 Patricia Moraes Rêgo.pdf: 1511056 bytes, checksum: 21108136b08107eeb212f5d74ed79ef7 (MD5) / Made available in DSpace on 2017-08-22T13:19:28Z (GMT). No. of bitstreams: 1 Patricia Moraes Rêgo.pdf: 1511056 bytes, checksum: 21108136b08107eeb212f5d74ed79ef7 (MD5) Previous issue date: 2007-08-03 / FAPEMA / In this work are proposed models and a convergence analysis of a hierarchical genetic algorithm for the linear quadratic regulator design loop recovery through LQG/LTR controllers. Models are oriented to the weighting and covariance matrices searching of the performance indices of the LQR and LQG design, respectively, and to the selection of the matrices for the LQR design loop recovery gain. The convergence analysis aims at promoting the enhancement of the algorithm performance, as well as to generate satisfactory solutions and speed up the convergence time. The algorithm performance is evaluated with respect to the e ects of an elitist strategy embodied into the algorithm and to variations in the values of some given parameters of the algorithm. The proposed methodology is evaluated in a multi-variable dynamical system representing an aircraft. / Propõe-se neste trabalho os modelos e a análise de convergência de um algoritmo genético hierárquico para recuperação da malha de projeto do regulador linear quadrático por controladores LQG/LTR (Linear Quadratic Gaussian/Loop Transfer Recovery). Os modelos dedicam-se à busca das matrizes de ponderações e covariâncias dos índices de desempenho dos projetos de controladores LQR (Linear Quadratic Regulator) e LQG (Linear Quadratic Gaussian), respectivamente, e à seleção de matrizes de ajuste para o ganho de recuperação da malha do projeto LQR. O objetivo da análise de convergência é promover melhorias no desempenho do algoritmo no sentido de gerar soluções satisfatórias e acelerar o tempo de convergência. O desempenho do algoritmo é avaliado em relação aos efeitos de uma estratégia elitista incorporada ao algoritmo e à variações nos valores de determinados parâmetros do algoritmo. A metodologia proposta é avaliada em um sistema dinâmico multivariável que representa uma aeronave.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-09-04T13:10:41Z No. of bitstreams: 1 Marcio Eduardo.pdf: 7939176 bytes, checksum: 3b90c4b32aeabafd3b87e4f3c36d2ed6 (MD5) / Made available in DSpace on 2017-09-04T13:10:41Z (GMT). No. of bitstreams: 1 Marcio Eduardo.pdf: 7939176 bytes, checksum: 3b90c4b32aeabafd3b87e4f3c36d2ed6 (MD5) Previous issue date: 2014-08-21 / The technique of linear control based on the minimization of a quadratic performance index using the second method of Lyapunov to guarantee the stability of the system, if this is controllable and observable. however, this technique is inevitably necessary to find the solution of the HJB or Riccati equation. The control system design online need, real time, to adjust your feedback gain to maintain a certain dynamic, it requires the calculation of the Riccati equation solution in each sampling generating a large computational load that can derail its implementation. This work shows an intelligent control system design that meets the optimal or suboptimal control action from the sensory data of process states and the instantaneous cost observed after each state transition. To find this optimal control action or policy, the approximate dynamic programming and adaptive critics are used, based on the parameterizations given by the problem of linear quadratic regulator (LQR), but without explicitly solving the associated Riccati equation. More specifically, the LQR problem is solved by four different methods which are the Dynamic Programming Heuristic, the Dual Heuristic Dynamic Programming, Action Dependent Dynamic Programming Heuristic and Action Dependent Dual Heuristic Dynamic Programming algorithms. However, these algorithms depend on knowledge of the value functions to derive the optimal control actions. These value functions with known structures have their parameters estimated using the least mean square family and Recursive Least Squares algorithms. Two processes that have the Markov property were used in the computational validation of the algorithms adaptive critics implemented, one corresponds to the longitudinal dynamics of an aircraft and the other to an electrical circuit. / A técnica de controle linear baseado na minimização de um índices de desempenho quadrático utilizando o segundo método de Liapunov garante a estabilidade do sistema, se este for controlável e observável. Por outro lado, nessa técnica inexoravelmente é necessário encontrar a solução da Equação Hamilton-Jacobi-Bellman (HJB) ou Riccati. Em projeto de sistema de controle online que necessita, em tempo real, alterar seus ganhos de retroação para manter uma certa dinâmica, impõe o cálculo da solução da equação de Riccati em cada instante de amostragem gerando uma grande carga computacional que pode inviabilizar sua implementação. Neste trabalho, mostra-se o projeto de um sistema de controle inteligente que encontra a ação de controle ótima ou subótima a partir de dados sensoriais dos estados do processo e do custo instantâneo observados após cada transição de estado. Para encontrar essa ação de controle ou política ótima, a programação dinâmica aproximada ou críticos adaptativos são utilizados, tendo como base as parametrizações dado pelo problema do regulador linear quadrático (LQR), mas sem resolver explicitamente a equação de Riccati associada. Mais especificamente, o problema do LQR é resolvido por quatro métodos distintos que são os algoritmos de Programação Dinâmica Heurística, a Programação Dinâmica Heurística Dual, a Programação Dinâmica Heurística Dependente de Ação e a Programação Dinâmica Heurística Dual Dependente de Ação. Entretanto, esses algoritmos dependem do conhecimento das funções valor para, assim, derivar as ações de controle ótimas. Essas funções valor com estruturas conhecidas tem seus parâmetros estimados utilizando os algoritmos da família dos mínimos quadrados médios e o algoritmo de Mínimos Quadrados Recursivo. Dois processos que obedecem à propriedade de Markov foram empregados na validação computacional dos algoritmos críticos adaptativos, um corresponde à dinâmica longitudinal de uma aeronave e o outro à de um circuito elétrico.

Modern control theory is today an interdisciplinary area of research. Just as much as this can be problematic, it also provides a rich research environment where practice and theory meet. This Thesis is conducted in the borderline between computing science (numerical analysis) and applied control theory. The design and analysis of a modern control system is a complex problem that requires high qualitative software to accomplish. Ideally, such software should be based on robust methods and numerical stable algorithms that provide quantitative as well as qualitative information. The introduction of the Thesis is dedicated to the underlying control theory and to introduce the reader to the main subjects. Throughout the Thesis, the theory is illustrated with several examples, and similarities and differences between the terminology from mathematics, systems and control theory, and numerical linear algebra are highlighted. The main contributions of the Thesis are structured in two parts, dealing with two mainly unrelated subjects. Part I is devoted to the qualitative information which is provided by the stratification of orbits and bundles of matrices, matrix pencils and system pencils. Before the theory of stratification is established the reader is introduced to different canonical forms which reveal the system characteristics of the model under investigation. A stratification reveals which canonical structures of matrix (system) pencils are near each other in the sense of small perturbations of the data. Fundamental concepts in systems and control, like controllability and observability of linear continuous-time systems, are considered and it is shown how these system characteristics can be investigated using the stratification theory. New results are presented in the form of the cover relations (nearest neighbours) for controllability and observability pairs. Moreover, the permutation matrices which take a matrix pencil in the Kronecker canonical form to the corresponding system pencil in (generalized) Brunovsky canonical form are derived. Two novel algorithms for determining the permutation matrices are provided. Part II deals with numerical methods for solving periodic Riccati differential equations (PRDE:s). The PRDE:s under investigation arise when solving the linear quadratic regulator (LQR) problem for periodic linear time-varying (LTV) systems. These types of (periodic) LQR problems turn up for example in motion planning of underactuated mechanical systems, like a humanoid robot, the Furuta pendulum, and pendulums on carts. The constructions of the nonlinear controllers are based on linear versions found by stabilizing transverse dynamics of the systems along cycles. Three different methods explicitly designed for solving the PRDE are evaluated on both artificial systems and stabilizing problems originating from experimental control systems. The methods are the one-shot generator method and two recently proposed methods: the multi-shot method (two variants) and the SDP method. As these methods use different approaches to solve the PRDE, their numerical behavior and performance are dependent on the nature of the underlying control problem. Such method characteristics are investigated and summarized with respect to different user requirements (the need for accuracy and possible restrictions on the solution time). / Modern reglerteknik är idag i högsta grad ett interdisciplinärt forskningsområde. Lika mycket som detta kan vara problematiskt, resulterar det i en stimulerande forskningsmiljö där både praktik och teori knyts samman. Denna avhandling är utförd i gränsområdet mellan datavetenskap (numerisk analys) och tillämpad reglerteknik. Att designa och analysera ett modernt styrsystem är ett komplext problem som erfordrar högkvalitativ mjukvara. Det ideala är att mjukvaran består av robusta metoder och numeriskt stabila algoritmer som kan leverera både kvantitativ och kvalitativ information.Introduktionen till avhandlingen beskriver grundläggande styr- och reglerteori samt ger en introduktion till de huvudsakliga problemställningarna. Genom hela avhandlingen illustreras teori med exempel. Vidare belyses likheter och skillnader i terminologin som används inom matematik, styr- och reglerteori samt numerisk linjär algebra. Avhandlingen är uppdelade i två delar som behandlar två i huvudsak orelaterade problemklasser. Del I ägnas åt den kvalitativa informationen som ges av stratifiering av mångfalder (orbits och bundles) av matriser, matrisknippen och systemknippen. Innan teorin för stratifiering introduceras beskrivs olika kanoniska former, vilka var och en avslöjar olika systemegenskaper hos den undersökta modellen. En stratifiering ger information om bl.a. vilka kanoniska strukturer av matrisknippen (systemknippen) som är nära varandra med avseende på små störningar i datat. Fundamentala koncept i styr- och reglerteori behandlas, så som styrbarhet och observerbarhet av linjära tidskontinuerliga system, och hur dessa systemegenskaper kan undersökas med hjälp av stratifiering. Nya resultat presenteras i form av relationerna för täckande (närmsta grannar) styrbarhets- och observerbarhets-par. Dessutom härleds permutationsmatriserna som tar ett matrisknippe i Kroneckers kanoniska form till motsvarande systemknippe i (generaliserade) Brunovskys kanoniska form. Två algoritmer för att bestämma dessa permutationsmatriser presenteras. Del II avhandlar numeriska metoder för att lösa periodiska Riccati differentialekvationer (PRDE:er). De undersökta PRDE:erna uppkommer när ett linjärt kvadratiskt regulatorproblem för periodiska linjära tidsvariabla (LTV) system löses. Dessa typer av (periodiska) regulatorproblem dyker upp till exempel när man planerar rörelser för understyrda (underactuated) mekaniska system, så som en humanoid (mänsklig) robot, Furuta-pendeln och en vagn med en inverterad (stående) pendel. Konstruktionen av det icke-linjära styrsystemet är baserat på en linjär variant som bestäms via stabilisering av systemets transversella dynamik längs med cirkulära banor. Tre metoder explicit konstruerade för att lösa PRDE:er evalueras på både artificiella system och stabiliseringsproblem av experimentella styrsystem. Metoderna är sk. en- och flerskotts metoder (one-shot, multi-shot) och SDP-metoden. Då dessa metoder använder olika tillvägagångssätt för att lösa en PRDE, beror dess numeriska egenskaper och effektivitet på det underliggande styrproblemet. Sådana metodegenskaper undersöks och sammanfattas med avseende på olika användares behov, t.ex. önskad noggrannhet och tänkbar begränsning i hur lång tid det får ta att hitta en lösning.

Networked embedded control systems are present almost everywhere. A recent trendis to introduce radio communication in these systems to increase mobility and flex-ibility. Network nodes, such as the sensors, are often simple devices with limitedcomputing and transmission power and low storage capacity, so an important prob-lem concerns how to optimize the use of resources to provide sustained overall sys-tem performance. The approach to this problem taken in the thesis is to analyzeand design the communication and control application layers in an integrated man-ner. We focus in particular on cross-layer design techniques for closed-loop controlover non-ideal communication channels, motivated by future control systems withvery low-rate and highly quantized sensor communication over noisy links. Severalfundamental problems in the design of source–channel coding and optimal controlfor these systems are discussed.The thesis consists of three parts. The first and main part is devoted to the jointdesign of the coding and control for linear plants, whose state feedback is trans-mitted over a finite-rate noisy channel. The system performance is measured by afinite-horizon linear quadratic cost. We discuss equivalence and separation proper-ties of the system, and conclude that although certainty equivalence does not holdin general it can still be utilized, under certain conditions, to simplify the overalldesign by separating the estimation and the control problems. An iterative opti-mization algorithm for training the encoder–controller pairs, taking channel errorsinto account in the quantizer design, is proposed. Monte Carlo simulations demon-strate promising improvements in performance compared to traditional approaches.In the second part of the thesis, we study the rate allocation problem for statefeedback control of a linear plant over a noisy channel. Optimizing a time-varyingcommunication rate, subject to a maximum average-rate constraint, can be viewedas a method to overcome the limited bandwidth and energy resources and to achievebetter overall performance. The basic idea is to allow the sensor and the controllerto communicate with a higher data rate when it is required. One general obstacle ofoptimal rate allocation is that it often leads to a non-convex and non-linear problem.We deal with this challenge by using high-rate theory and Lagrange duality. It isshown that the proposed method gives a good performance compared to some otherrate allocation schemes.In the third part, encoder–controller design for Gaussian channels is addressed.Optimizing for the Gaussian channel increases the controller complexity substan-tially because the channel output alphabet is now infinite. We show that an efficientcontroller can be implemented using Hadamard techniques. Thereafter, we proposea practical controller that makes use of both soft and hard channel outputs. / QC 20100623

A key element of hydrologic routing models is the storage-discharge relationship assumed to follow a certain mathematical form, usually a linear or a power function, the parameters of which are calibrated based on existing inflow-outflow data. While this assumption simplifies the model calibration process, it also constrains the models to operate by this function throughout their flow range. In view of the complex and nonlinear river flow behavior, this approximation undoubtedly introduces errors. This research presents a new hydrologic river routing approach that is not limited by the above assumption. River reaches are modeled as cascades of interacting conceptual reservoirs, with storage-discharge functions identified by the data. A novel parameter estimation approach has been developed to identify these functions and all other model parameters based on control theory concepts. After calibration, these functions indeed exhibit different mathematical forms at different regions of their active variation range. The new approach is applied and successfully demonstrated in real world reservoir and river routing applications from the Nile River Basin. A Bayesian forecasting scheme was also developed that uses the new approach to generate flow forecasts with explicit uncertainty characterization.

This thesis applies digital repetitive control to a single-phase DC-to-AC converter, with some proposed designs to improve stability and enhance performance of the converter under various load variations. A practical DC-to-AC converter is required to convert DC power to stable AC power with low harmonic distortion when attached to various linear or nonlinear loads. This thesis combines repetitive control with feedback dithering modulation and optimal state feedback to control the converter. The repetitive control is responsible for regulating output power and eliminating harmonics, while the feedback dithering modulation for switching the power transistors with reduced switching noise and the state feedback for stabilizing the converter under various load variations. The presented control and modulation schemes of the power converter are implemented on an FPGA (Field Programmable Gate Array). The experiments confirm the excellent performance and robustness of the converter, indicating a total harmonic distortion of less than 0.5% for the converter when attached to various linear or nonlinear loads.