In this thesis a robust nonlinear tracking is proposed for a class of single machine connected to an infinite bus (SMIB) systems. Designing of the controller is based on the backstepping control technique, where designer interlaces the choice of L yapunov functions in order to design the controller and analyze the stability of the power angle and rotating speed of the generator. Nonlinear models are considered directly in the designing process, hence neglecting the effects of nonlinear terms in the plant can be avoided, which may also improve the robustness of controlled system¡¦s transient stability. In order to enhance the applicability of the proposed control scheme, the perturbations that may encountered in the system are considered, and adaptive laws are embedded in the controllers so that the upper bound of perturbations need not to be known beforehand. Two numerical examples are given to illustrate the feasibility of the proposed control scheme.

Une stratégie de commande tolérante aux fautes active pour des systèmes suractionnés est présentée dans ce mémoire de thèse. Elle est formée de 4 étapes : détection rapide du défaut, activation d’une commande tolérante aux fautes qui assure le suivi de trajectoire du système en présence du défaut, localisation précise du défaut et finalement reconfiguration du système en déconnectant ou en bloquant dans une position déterminée, le composant défaillant. Cette stratégie de commande s’applique à un véhicule autonome de type 2WS4WD : lorsque la déviation latérale du véhicule dépasse un seuil de sécurité dynamique, une commande tolérante aux fautes basée sur la génération de références est activée. Son objectif est d’assurer la redistribution des tâches au niveau des actionneurs sains, non utilisés en fonctionnement normal, pour compenser l’effet du défaut. La loi de commande est élaborée en utilisant la théorie de Lyapunov et la technique du backstepping et calculée par deux boucles interconnectées. La première boucle, appelée boucle externe, calcule les nouveaux objectifs locaux nécessaires pour atteindre l’objectif global du système. La second boucle, appelée boucle interne, calcule la loi de commande nécessaire pour assurer le suivi des objectifs locaux élaborés dans la boucle externe. Un algorithme de localisation précise de défaut est ensuite appliqué pour déterminer le composant défaillant. Une fois ce composant identifié, le système suractionné est reconfiguré en utilisant uniquement les composants sains. Les algorithmes de diagnostic et de commande tolérante aux fautes sont finalement validés en utilisant une co-simulation des logiciels CarSim et Matlab/Simulink. / An active fault tolerant control (AFTC) strategy for overactuated systems is presented in this thesis. It consists of four steps: detecting very quickly the fault, activating a fault tolerant control law for preserving the stability of the overactuated system in presence of the fault, localizing precisely the faulty component, and finally reconfiguring the system by maintaining only the healthy components. This strategy is applied to an autonomous 2WS4WD vehicle : when the vehicle’s lateral deviation exceeds a dynamic security threshold, the fault tolerant control algorithm is activated. It is based on a dynamic reference generation and consists in controlling the redundant actuators which are not used in normal behavior. The control law used for this task is designed using Lyapunov theory and backstepping technique. It consists of two interconnected control loops: an outer loop and an inner loop. The outer loop ensures the computation of dynamic references necessary for preserving the trajectory tracking of the vehicle. The inner loop ensures the tracking of the dynamic references generated in the outer loop. A fault isolation module is then applied to determine precisely the faulty component. Once it is isolated, the system is controlled by using only healthy components. The diagnosis and fault tolerant control schemes are validated on a realistic vehicle model using a co-simulation between CarSim and Matlab/Simulink softwares.

In this thesis the synchronization of two different chaotic systems with matched and mismatched perturbations are developed by utilizing adaptive backstepping control technique. The adaptive mechanisms embeded in the proposed control scheme is used to adapt the unknown upper bounds of the perturbations. The resultant robust backstepping tracking controller with adaptive mechanisms can indeed drive the trajectories of the slave system to track those of the master system. Two numerical examples and simulations are given to illustrate the correctness of theoretical analyses.

The last decade has seen significant advances in the development of Vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs). The emergence of enabling technologies, in addition to the practical usefulness of such systems has driven their development to a point where numerous technology demonstrators and commercial products are now in existence. Of particular interest has been the development of small scale, VTOL UAVs commonly referred to as mini and micro-VTOL UAVs. The versatility and agility of such vehicles offers great potential for the use in clustered, urban environments. Despite recent advancements, the autonomous navigation of VTOL UAVs remains a very challenging research area. The dynamics of VTOL UAVs are heavily nonlinear, underactuated and non-minimum phase. This, coupled with the aggressive maneuvers that such vehicles are expected to execute provides a stimulating problem in dynamic control. This is particularly true in the case of micro-VTOL UAVs. The fast, nonlinear nature of these systems render classical, linear control approaches inadequate. The past twenty years has seen great interest in the development of nonlinear control strategies. This has led to the emergence of a number of standard design tools, most notably feedback linearisation and Lyapunov-based, backstepping approaches. Such design techniques offer a framework for the derivation of model based control laws capable of achieving global stabilisation and trajectory tracking control for heavily nonlinear systems. Recently, there has been significant interest in the application of such nonlinear control paradigms for the stabilisation and control of VTOL UAVs. The aim of this thesis is to further the application and analysis of nonlinear control design techniques for the control of VTOL UAVs. In particular, focus is placed on Lyapunov-based, backstepping-type control approaches. The first half of this thesis investigates Lyapunov-based control strategies that cast the closed-loop VTOL dynamics into a globally stable, cascade structure. This work was directly inspired by, and builds on, a variety of previously published works. Firstly, an alternative design approach to that previously published is presented, resulting in an improved closed-loop dynamic structure. Although inspired by the VTOL system, this idea may be generalised for the control of a broad class of systems, and is presented as such. A singularity issue arising in the cascade control of VTOL vehicles is then investigated, and a novel approach to overcome this issue is formulated. The second half of this thesis is dedicated to the trajectory tracking control of VTOL UAVs at velocities where the influence of aerodynamics is significant. In general, the aerodynamic models of VTOL UAVs are heavily nonlinear and poorly known. The use of such models in a backstepping framework that uses explicit differentiation of these models for dynamic inversion is questioned, due to the potential sensitivity of such nonlinear models. Consequently, an alternative approach utilising coupled filters to avoid such sensitivity issues is proposed. All control designs formulated in this thesis are accompanied by proofs guaranteeing their global stability, and numerical simulations demonstrating their time domain response characteristics. / http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1298413 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2007

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With an increased push for commercial autonomous cars, the demand of high speed systems capable of performing in unstructured driving environments is growing. In this thesis, the behavior of a bio-inspired predator prey model is considered to stimulate a more organic response to obstacles and a moving target than existing algorithms. However, the current predator prey model has a disconnect between the desired velocities commanded and the torque signals provided to the motors due the dynamics of the vehicle not accounted for. This causes the vehicle to derail from its intended trajectory at sharp turns. In this study, we start by adding dynamic behavior to the unicycle model to account for the varying dynamics of the vehicle. A backstepping algorithm is developed to connect the predator-prey model commanding desired velocities to an appropriate torque controller for the motors of the vehicle. To account for the unknown dynamic model parameters an adaptive control approach is utilized. Three different controllers are developed and evaluated. Out of the three, the indirect MRAC backstepping controller is deemed unsuitable due to its limitations with handling unknown parameter structure. The direct MRAC backstepping is deemed suitable and therefore simulated and implemented on the vehicle. The newly derived controller is able to overcome the disconnect and allow the vehicle to optimally track its trajectory for a velocity range of 1 m/s to 9 m/s despite varying dynamics. Lastly, the L1 adaptive backstepping controller is introduced and simulated to provide an alternative, more robust solution to the direct MRAC backstepping controller. / Master of Science

Sistemas de Posicionamento Dinâmico (SPD) são sistemas de controle que visam assegurar que um veículo oceânico se mantenha em uma determinada posição ou acompanhe uma trajetória de referência, mediante o emprego exclusivo de seus propulsores. Um SPD pode ser desmembrado em vários módulos específicos, com funções bem determinadas. Os módulos mais importantes são os sistemas de medição de posição e aproamento, o estimador de estados, o controlador e o algoritmo de alocação de empuxos. Atualmente, o Filtro de Kalman Estendido (FKE) é o estimador padrão para todos os SPD comercialmente disponíveis. Entretanto, o emprego do FKE implica em uma série de desvantagens. A sintonização do sistema é demorada e difícil, em função do elevado número de parâmetros de sintonização. Estabilidade assintótica global não pode ser conferida ao sistema. Adicionalmente, é necessário aplicar a técnica de programação de ganhos, uma vez que as equações cinemáticas de movimento do modelo devem ser linearizadas para aproximadamente 36 ângulos de guinada. A fim de eliminar estes óbices, o presente estudo propõe o desenvolvimento de um SPD totalmente não-linear, composto por um observador passivo não-linear e um controlador não-linear backstepping. / Dynamic Positioning Systems (DPS) are control systems used to maintain the vessel on a desired position or pre-defined path exclusively by means of active thrusters. A DPS can be separated into a set of dedicated modules with designated tasks. The most significant modules are the position and heading measurement systems, the state estimator, the controller and the thrust allocation algorithm. Nowadays, the Extended Kalman Filter (EKF) is the standard state estimator for all commercial DPS. However, the EKF technique presents several drawbacks. There is a large number of tuning parameters which requires a time-consuming tuning procedure. Global asymptotic stability cannot be assured to the system. Furthermore, it requires the use of a gain-scheduling technique, since the model is linearized about approximately 36 yaw angles due to the kinematics equations of motions. To solve these problems, this study proposes the development of a fully nonlinear DPS comprising a passive nonlinear observer and a nonlinear backstepping controller.

Unmanned Aerial Vehicles (UAV) control has become a very important point of scientific study. The control design challenges of a UAV make it one of the most researched areas in modern control applications. This thesis specifically chooses the Quadrotor as the UAV platform. Considering the quadrotor has 4 rotors and 6 degrees of freedom, it is an underactuated system and is dynamically unstable that has to be stabilized by a suitable control algorithm in order to operate autonomously. This thesis focuses on the quaternion representation of the quadrotor system dynamics and develops an adaptive control for its trajectory tracking problem. The control design uses the certainty equivalence principle where adaptive tracking controls are designed separately for each of the translational and rotational subsystems. With this approach, the success of the outer loop translational control relies on the fast convergence of the inner loop rotational control in order to guarantee the system’s stability while achieving the tracking objective. For the translational subsystem in the outer loop, a modified geometric control technique is considered with an adaptive component for the estimation of the uncertain mass of the quadrotor. For the rotational subsystem in the inner loop a backstepping based control design is adopted due to its systematic design and intuitive approach. An adaptive component is further integrated with it to estimate the integrated components of the uncertain Moment of Inertia matrix and other constant parameters in the system dynamics to guarantee the stability of the inner loop system while achieving the tracking objective. Furthermore, a complete backstepping control design methodology is presented which overcomes the issues of certainty equivalence principle where the inner loop needs to execute significantly faster than the outer loop to stabilize the system.

Sistemas de Posicionamento Dinâmico (SPD) são sistemas de controle que visam assegurar que um veículo oceânico se mantenha em uma determinada posição ou acompanhe uma trajetória de referência, mediante o emprego exclusivo de seus propulsores. Um SPD pode ser desmembrado em vários módulos específicos, com funções bem determinadas. Os módulos mais importantes são os sistemas de medição de posição e aproamento, o estimador de estados, o controlador e o algoritmo de alocação de empuxos. Atualmente, o Filtro de Kalman Estendido (FKE) é o estimador padrão para todos os SPD comercialmente disponíveis. Entretanto, o emprego do FKE implica em uma série de desvantagens. A sintonização do sistema é demorada e difícil, em função do elevado número de parâmetros de sintonização. Estabilidade assintótica global não pode ser conferida ao sistema. Adicionalmente, é necessário aplicar a técnica de programação de ganhos, uma vez que as equações cinemáticas de movimento do modelo devem ser linearizadas para aproximadamente 36 ângulos de guinada. A fim de eliminar estes óbices, o presente estudo propõe o desenvolvimento de um SPD totalmente não-linear, composto por um observador passivo não-linear e um controlador não-linear backstepping. / Dynamic Positioning Systems (DPS) are control systems used to maintain the vessel on a desired position or pre-defined path exclusively by means of active thrusters. A DPS can be separated into a set of dedicated modules with designated tasks. The most significant modules are the position and heading measurement systems, the state estimator, the controller and the thrust allocation algorithm. Nowadays, the Extended Kalman Filter (EKF) is the standard state estimator for all commercial DPS. However, the EKF technique presents several drawbacks. There is a large number of tuning parameters which requires a time-consuming tuning procedure. Global asymptotic stability cannot be assured to the system. Furthermore, it requires the use of a gain-scheduling technique, since the model is linearized about approximately 36 yaw angles due to the kinematics equations of motions. To solve these problems, this study proposes the development of a fully nonlinear DPS comprising a passive nonlinear observer and a nonlinear backstepping controller.

In this dissertation, we develop feedback control strategies that can be used for evacuating people. Pedestrian models are based on macroscopic or microscopic behavior. We use the macroscopic modeling approach, where pedestrians are treated in an aggregate way and detailed interactions are overlooked. The models representing evacuation dynamics are based on the laws of conservation of mass and momentum and are described by nonlinear hyperbolic partial differential equations. As such the system is distributed in nature. We address the design of feedback control for these models in a distributed setting where the problem of control and stability is formulated directly in the framework of partial differential equations. The control goal is to design feedback controllers to control the movement of people during evacuation and avoid jams and shocks. We design the feedback controllers for both diffusion and advection where the density of people diffuses as well as moves in a specified direction with time. In order to achieve this goal we are assuming that the control variables have no bounds. However, it is practically impossible to have unbounded controls so we modify the controllers in order to take the effect of control saturation into account. We also discuss the feedback control for these models in presence of uncertainties where the goal is to design controllers to minimize the effect of uncertainties on the movement of people during evacuation. The control design technique adopted in all these cases is feedback linearization which includes backstepping for higher order two-equation models, Lyapunov redesign for uncertain models and robust backstepping for two-equation uncertain models. The work also focuses on abstraction of evacuation system which focuses on obtaining models with lesser number of partial differential equations than the original one. The feedback control design of a higher level two-equation model is more difficult than the lower order one-equation model. Therefore, it is desirable to perform control design for a simpler abstracted model and then transform control design back to the original model. / Ph. D.