The United States trucking industry is immense. Employing over three million drivers and traveling to every city in the country. Semi-Trucks travel millions of miles each week and encompass roads that civilians travel on. These vehicles should be safe and allow efficient travel for all. Autonomous vehicles have been discussed in controls for many decades. Now fleets of autonomous vehicles are beginning their integration into society. The ability to create an autonomous system requires domain and system specific knowledge. Approaches to implement a fully autonomous vehicle have been developed using different techniques in control systems such as Kalman Filters, Neural Networks, Model Predictive Control, and Adaptive Control. However some of these control techniques require superb models, immense computing power, and terabytes of storage. One way to circumvent these issues is by the use of an adaptive control scheme. Adaptive control systems allow for an existing control system to self-tune its performance for unknown variables i.e. when an environment changes. In this thesis a LQR error state control system is derived and shown to maintain a magnitude of 15 cm of steady state error from the center-line of the road. In addition a proposed LQR-MRAC controller is used to test the robustness of a lane-keeping control system. The LQR-MRAC controller was able to improve its transient response peak error from the center-line of the road of the tractor and the trailer by 9.47 [cm] and 7.27 [cm]. The LQR-MRAC controller increased tractor steady state error by 0.4 [cm] and decreased trailer steady state error by 1 [cm]. The LQR-MRAC controller was able to outperform modern control techniques and can be used to improve the response of the tractor-trailer system to handle mass changes in its environment.

Though multirotor unmanned aerial vehicles (UAVs) have become widely used during the past decade, challenges in autonomy have prevented their widespread use when moving vehicles act as their base stations. Emerging use cases, including maritime surveillance, package delivery and convoy support, require UAVs to autonomously operate in this scenario. This thesis presents improved solutions to both the state estimation and control problems that must be solved to enable robust, autonomous landing of multirotor UAVs onto moving vehicles.Current state-of-the-art UAV landing systems depend on the detection of visual fiducial markers placed on the landing target vehicle. However, in challenging conditions, such as poor lighting, occlusion, or extreme motion, these fiducial markers may be undected for significant periods of time. This thesis demonstrates a state estimation algorithm that tracks and estimates the locations of unknown visual features on the target vehicle. Experimental results show that this method significantly improves the estimation of the state of the target vehicle while the fiducial marker is not detected.This thesis also describes an improved control scheme that enables a multirotor UAV to accurately track a time-dependent trajectory. Rooted in Lie theory, this controller computes the optimal control signal based on an error-state formulation of the UAV dynamics. Simulation and hardware experiments of this control scheme show its accuracy and computational efficiency, making it a viable solution for use in a robust landing system.

No description available.

Mechanical systems operate under parametric and external excitation uncertainties. The polynomial chaos approach has been shown to be more efficient than Monte Carlo approaches for quantifying the effects of such uncertainties on the system response. This work uses the polynomial chaos framework to develop new methodologies for the simulation, parameter estimation, and control of mechanical systems with uncertainty. This study has led to new computational approaches for parameter estimation in nonlinear mechanical systems. The first approach is a polynomial-chaos based Bayesian approach in which maximum likelihood estimates are obtained by minimizing a cost function derived from the Bayesian theorem. The second approach is based on the Extended Kalman Filter (EKF). The error covariances needed for the EKF approach are computed from polynomial chaos expansions, and the EKF is used to update the polynomial chaos representation of the uncertain states and the uncertain parameters. The advantages and drawbacks of each method have been investigated. This study has demonstrated the effectiveness of the polynomial chaos approach for control systems analysis. For control system design the study has focused on the LQR problem when dealing with parametric uncertainties. The LQR problem was written as an optimality problem using Lagrange multipliers in an extended form associated with the polynomial chaos framework. The solution to the Hâ problem as well as the H2 problem can be seen as extensions of the LQR problem. This method might therefore have the potential of being a first step towards the development of computationally efficient numerical methods for Hâ design with parametric uncertainties. I would like to gratefully acknowledge the support provided for this work under NASA Grant NNL05AA18A. / Ph. D.

"The recent years have seen the innovative system integration of a great many actuator technologies, such as point force actuators for space vehicle applications and the use of single fire actuators; such as pyrocharges to guide a free falling bomb to it’s target. The inherent limitations of these developments, such as nonlinear behavior under extreme environments and/or prolonged/repeated usage leading to a relaxation time component between firing of actuators and inherent system power limitations, have resulted in greater need for sophisticated control algorithms that allow for optimal switching between various actuators in any given embedded configuration so as to achieve the best possible performance of the system. The objective of this investigation is to offer a proof of concept experimental verification of a real time control algorithm, which switches between online piezoelectric actuators, employed for vibration control in an aluminum beam with fixed boundary conditions. In this investigation at a given interval of time, only one actuator is activated and the rest are kept dormant. The reason is to demonstrate the better vibration alleviation characteristics realized in switching between actuators depending on the state of the system, over the use of a single actuator that is always in fire mode. This effect is particularly pronounced in controlling systems affected by spatiotemporal disturbances. The algorithm can be easily adapted for various design configurations or system requirements. The optimality of switching is with respect to the minimal cost of an LQR performance index that corresponds to each actuator. Computer simulations with repeatable disturbance profiles, revealed that this algorithm offered better performance over the non-switched case. Performance measures employed were the time varying total energy norm of the dynamic system and position traces at any particular location on the beam. This algorithm was incorporated on a dSPACE rapid prototyping platform along with suitable hardware. Experimental and simulation results are discussed. "

Com o aperfeiçoamento de materiais compósitos de alto desempenho, surge a possibilidade do desenvolvimento de estruturas inteligentes, onde atuadores e sensores piezelétricos estão integrados na estrutura com sistemas de controle adequados para a atenuação de vibrações. Projetos multidisciplinares se tornam cada vez mais complexos e sofisticados, envolvendo diversas fontes de incertezas que devem ser analisadas e quantificadas. O escopo principal desse trabalho visa o estudo da propagação de incertezas em estruturas de materiais compósitos laminados com atuadores e sensores piezelétricos, onde entradas e parâmetros do projeto podem ser fontes aleatórias e/ou nebulosas. Para atingir esse objetivo é adotada a metodologia fuzzy, com a aplicação de otimização de cortes-α. Essa técnica é utilizada na presença de informações vagas ou imprecisas acerca da aleatoriedade presente. Nesse estudo projetam-se, através do método dos elementos finitos, estruturas em forma de placa e casca de material compósito laminado com atuadores e sensores piezelétricos acoplados, controlados pelos reguladores Linear Quadratic Regulator (LQR) e Linear Quadratic Gaussian (LQG). Inicialmente são realizados estudos de otimização para encontrar a melhor localização dos componentes piezelétricos pelos Gramianos de controlabilidade e observabilidade, assim como os fatores de ponderação das leis de controle. O desenvolvimento é realizado no espaço modal reduzido visando um melhor desempenho computacional. As métricas escolhidas para avaliação do controle de vibração e análise das saídas incertas do sistema são baseadas nas energias cinética, potencial e elétrica. Também apresentam-se estudos de envelopes relacionados ao deslocamentos e às frequências naturais da estrutura devido às incertezas. Os resultados mostraram que as otimizações por corte-α para tratar números fuzzy nesse tipo de problema são robustas e eficientes, encontrando-se valores extremos das saídas desejadas. Além de ser um método não intrusivo, também pode ser utilizado em problemas com um número elevado de parâmetros incertos como entrada. / The possibility of developments of smart structures arises with high performance composite materials improvements, where piezoelectric actuators and sensors are embedded into the structures, following a suitable control laws for vibration attenuation. Multidisciplinary projects are becoming highly complex and sophisticated, involving several sources of uncertainty that should be analyzed and quantified. The main objective for this work is to study the uncertainty propagation in composite laminate structures with embedded piezoelectric actuators and sensors, considering random and/or fuzzy sources for the inputs and design parameters. To accomplish this objective, it is adopted the fuzzy α-cut optimizations methodology. This technique is used when the available information related to the actual randomness is vague or imprecise. In this study, laminated composite shells and plates structures are designed and analyzed by the finite element method, where embedded piezoelectric actuators and sensors controlled by Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) are present. Initially, optimization analyses are executed to find the best arrangement for the piezoelectric material using controllability and observability Gramians metrics, as well as the best controller parameters. This study is developed in the reduced modal space looking for computational costs savings. The chosen rating metrics for the vibration control and uncertainty analysis are based on kinetic, potential and electrical energies. Structural displacements and natural frequency envelopes due uncertainty are also studied and presented. The results have shown that the fuzzy α-cut optimizations methodology is robust and efficient to find extreme values for the sought outputs. In addition to being a non-intrusive method, it is also able to deal with a large number of uncertain input parameters.

In this thesis, control and guidance algorithms for unmanned sea surface vehicles are studied. To design control algorithms of different complexity, first a mathematical model for an unmanned sea surface vehicle is derived. The dynamical and kinematical equations for a sea surface vehicle are obtained, and they are adapted to real life conditions with necessary additions and simplifications. The forces and torques effecting on the vehicle are investigated in detail. Control algorithms for under-actuated six degrees-of-freedom model are designed. PID and LQR controllers are implemented to attain desired surge speed and yaw position. The autopilots are designed and their performances are compared. Based on the autopilots, a guidance algorithm is implemented to achieve desired motions of the vehicle. An obstacle avoidance algorithm is proposed for safe motion among the obstacles. A next-point generation algorithm is designed to direct the vehicle to the most appropriate next way-point if the one ahead is missed. The effects of disturbances on the motion of the vehicle are studied thoroughly on simulation results. PID controller for an unmanned sea surface vehicle is implemented on ArduPilot Mega v1.4 cart controlling a Traxxas Spartan model boat. The performance of the controller is validated. Simulations and experimental results are provided.

Com o aperfeiçoamento de materiais compósitos de alto desempenho, surge a possibilidade do desenvolvimento de estruturas inteligentes, onde atuadores e sensores piezelétricos estão integrados na estrutura com sistemas de controle adequados para a atenuação de vibrações. Projetos multidisciplinares se tornam cada vez mais complexos e sofisticados, envolvendo diversas fontes de incertezas que devem ser analisadas e quantificadas. O escopo principal desse trabalho visa o estudo da propagação de incertezas em estruturas de materiais compósitos laminados com atuadores e sensores piezelétricos, onde entradas e parâmetros do projeto podem ser fontes aleatórias e/ou nebulosas. Para atingir esse objetivo é adotada a metodologia fuzzy, com a aplicação de otimização de cortes-α. Essa técnica é utilizada na presença de informações vagas ou imprecisas acerca da aleatoriedade presente. Nesse estudo projetam-se, através do método dos elementos finitos, estruturas em forma de placa e casca de material compósito laminado com atuadores e sensores piezelétricos acoplados, controlados pelos reguladores Linear Quadratic Regulator (LQR) e Linear Quadratic Gaussian (LQG). Inicialmente são realizados estudos de otimização para encontrar a melhor localização dos componentes piezelétricos pelos Gramianos de controlabilidade e observabilidade, assim como os fatores de ponderação das leis de controle. O desenvolvimento é realizado no espaço modal reduzido visando um melhor desempenho computacional. As métricas escolhidas para avaliação do controle de vibração e análise das saídas incertas do sistema são baseadas nas energias cinética, potencial e elétrica. Também apresentam-se estudos de envelopes relacionados ao deslocamentos e às frequências naturais da estrutura devido às incertezas. Os resultados mostraram que as otimizações por corte-α para tratar números fuzzy nesse tipo de problema são robustas e eficientes, encontrando-se valores extremos das saídas desejadas. Além de ser um método não intrusivo, também pode ser utilizado em problemas com um número elevado de parâmetros incertos como entrada. / The possibility of developments of smart structures arises with high performance composite materials improvements, where piezoelectric actuators and sensors are embedded into the structures, following a suitable control laws for vibration attenuation. Multidisciplinary projects are becoming highly complex and sophisticated, involving several sources of uncertainty that should be analyzed and quantified. The main objective for this work is to study the uncertainty propagation in composite laminate structures with embedded piezoelectric actuators and sensors, considering random and/or fuzzy sources for the inputs and design parameters. To accomplish this objective, it is adopted the fuzzy α-cut optimizations methodology. This technique is used when the available information related to the actual randomness is vague or imprecise. In this study, laminated composite shells and plates structures are designed and analyzed by the finite element method, where embedded piezoelectric actuators and sensors controlled by Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) are present. Initially, optimization analyses are executed to find the best arrangement for the piezoelectric material using controllability and observability Gramians metrics, as well as the best controller parameters. This study is developed in the reduced modal space looking for computational costs savings. The chosen rating metrics for the vibration control and uncertainty analysis are based on kinetic, potential and electrical energies. Structural displacements and natural frequency envelopes due uncertainty are also studied and presented. The results have shown that the fuzzy α-cut optimizations methodology is robust and efficient to find extreme values for the sought outputs. In addition to being a non-intrusive method, it is also able to deal with a large number of uncertain input parameters.

Este trabalho apresenta uma metodologia de otimização topológica de atuadores piezelétricos em estruturas compostas laminada com o objetivo de atenuar as vibrações estruturais induzidas por excitações externas. Para isso, utiliza-se técnicas de controle ótimo, como o regulador linear quadrático (LQR) e o controlador linear quadrático gaussiano (LQG). Os estados não mensuráveis são estimados através do uso de observadores de estados de ordem completa, usando o filtro de Kalman para a escolha ótima da matriz de ganhos do observador de estados. O problema de otimização topológica é formulado para a localização ótima do atuador piezelétrico composto MFC (Macro Fiber Composite) na camada ativa da placa, determinando a localização mais vantajosa do material MFC através da maximização do índice de controlabilidade. Para o modelo estrutural, é proposto neste trabalho um modelo para a interação entre o atuador MFC e a estrutura. Assume-se que o MFC é uma das lâminas de material ortotrópico que sofre uma deformação inicial a partir da aplicação de um potencial elétrico e que essa deformação terá efeitos sobre o restante da estrutura. Dessa maneira, não é necessário modelar o campo elétrico gerado através dos eletrodos, uma vez que o efeito eletromecânico é considerado analiticamente. A rigidez e a massa do atuador MFC são considerados no modelo estrutural. Os resultados numéricos mostram que o modelo estrutural proposto para representar a interação entre o atuador MFC e a estrutura apresenta boa concordância com resultados experimentais e numéricos encontrados. Além disso, os resultados mostram que a partir do posicionamento ótimo do atuador MFC na estrutura, a técnica de controle implementada permite atenuar as vibrações estruturais. As simulações para uma força de um degrau unitário permitem concluir que a estratégia de controle usando o controlado LQG apresenta melhor desempenho em termos de tempo de assentamento, sobre resposta, amortecimento e sinal de controle, quando comparado com o controlador LQR. / This work presents a topologic optimization methodology of piezoelectric actuators in laminated composite structures with the objective of controlling external perturbation induced by structural vibrations. The Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) optimal control techniques are used. The states are estimated through of the full order state observers, using the Kalman filter to the observer gain matrix. The topology optimization is formulated to find the optimum localization of the Macro Fiber Composite (MFC) active piezoelectric patch, determining the most advantageous location of the MFC, through of the maximization of the controllability index. For the structural model, this work proposes a simplified MFC/structure interaction model. It is assumed that the MFC is one of the orthotropic material layers which has an initial strain arising from the application of an electric potential; this strain acts on the remainder of the structure. This way, modeling the electromechanical interaction between the piezoelectric material and the electric field is unnecessary because this effect is considered analytically. Both the stiffness and the mass of the MFC are taken into account in the structural model. Numerical results show that proposed MFC-structure interaction model presents good agreement with experiments and numerical simulations of models that uses the electromechanical effect. Actuator location optimization results show that the technique implemented improves the structural vibration damping. The response simulations to an unit step force allows to conclude that the control strategy using the LQG controller presents better performance in terms of settling time, overshoot, damping and control signal energy when compared to the LQR controller.

Com o aperfeiçoamento de materiais compósitos de alto desempenho, surge a possibilidade do desenvolvimento de estruturas inteligentes, onde atuadores e sensores piezelétricos estão integrados na estrutura com sistemas de controle adequados para a atenuação de vibrações. Projetos multidisciplinares se tornam cada vez mais complexos e sofisticados, envolvendo diversas fontes de incertezas que devem ser analisadas e quantificadas. O escopo principal desse trabalho visa o estudo da propagação de incertezas em estruturas de materiais compósitos laminados com atuadores e sensores piezelétricos, onde entradas e parâmetros do projeto podem ser fontes aleatórias e/ou nebulosas. Para atingir esse objetivo é adotada a metodologia fuzzy, com a aplicação de otimização de cortes-α. Essa técnica é utilizada na presença de informações vagas ou imprecisas acerca da aleatoriedade presente. Nesse estudo projetam-se, através do método dos elementos finitos, estruturas em forma de placa e casca de material compósito laminado com atuadores e sensores piezelétricos acoplados, controlados pelos reguladores Linear Quadratic Regulator (LQR) e Linear Quadratic Gaussian (LQG). Inicialmente são realizados estudos de otimização para encontrar a melhor localização dos componentes piezelétricos pelos Gramianos de controlabilidade e observabilidade, assim como os fatores de ponderação das leis de controle. O desenvolvimento é realizado no espaço modal reduzido visando um melhor desempenho computacional. As métricas escolhidas para avaliação do controle de vibração e análise das saídas incertas do sistema são baseadas nas energias cinética, potencial e elétrica. Também apresentam-se estudos de envelopes relacionados ao deslocamentos e às frequências naturais da estrutura devido às incertezas. Os resultados mostraram que as otimizações por corte-α para tratar números fuzzy nesse tipo de problema são robustas e eficientes, encontrando-se valores extremos das saídas desejadas. Além de ser um método não intrusivo, também pode ser utilizado em problemas com um número elevado de parâmetros incertos como entrada. / The possibility of developments of smart structures arises with high performance composite materials improvements, where piezoelectric actuators and sensors are embedded into the structures, following a suitable control laws for vibration attenuation. Multidisciplinary projects are becoming highly complex and sophisticated, involving several sources of uncertainty that should be analyzed and quantified. The main objective for this work is to study the uncertainty propagation in composite laminate structures with embedded piezoelectric actuators and sensors, considering random and/or fuzzy sources for the inputs and design parameters. To accomplish this objective, it is adopted the fuzzy α-cut optimizations methodology. This technique is used when the available information related to the actual randomness is vague or imprecise. In this study, laminated composite shells and plates structures are designed and analyzed by the finite element method, where embedded piezoelectric actuators and sensors controlled by Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) are present. Initially, optimization analyses are executed to find the best arrangement for the piezoelectric material using controllability and observability Gramians metrics, as well as the best controller parameters. This study is developed in the reduced modal space looking for computational costs savings. The chosen rating metrics for the vibration control and uncertainty analysis are based on kinetic, potential and electrical energies. Structural displacements and natural frequency envelopes due uncertainty are also studied and presented. The results have shown that the fuzzy α-cut optimizations methodology is robust and efficient to find extreme values for the sought outputs. In addition to being a non-intrusive method, it is also able to deal with a large number of uncertain input parameters.