Vehicle stability is an important consideration in vehicle design. When driver intervention is insufficient, safety can be improved by the addition of vehicle stability control (VSC). Typical vehicle stability controllers are designed using a linearized vehicle model and an assumed set of parameters. However, some parameters like mass and inertial properties may not be constant between operations. To recover controller performance in the presence of unknown parameters, adaptive estimates can be developed. This thesis seeks to implement a model reference adaptive controller for yaw rate and side slip control and to evaluate any implementation issues that may arise. A linearized vehicle model is used for controller design via a Lyapunov approach and a combined front wheel steering (FWS) and direct yaw control (DYC) controller is developed. The combined FWS+DYC controller is tested in a low friction double lane change with initial parameter estimation error. The FWS+DYC controller was found to be robust to parameter changes, and the adaptive parameter estimates did not provide any noticeable improvement over the non-adaptive case. A four wheel steering (4WS) controller is developed by a similar approach and tested under the same conditions. Both controllers were found to be effective at stabilizing the vehicle. An unexpected finding was that though the combined FWS+DYC controller was effective even in low friction conditions with parameter errors, the required motor torque was very large and oscillated rapidly. This was diminished through the addition of a low pass filter on the controller yaw moment output, but could not be removed entirely. / text

The new vision for space exploration will focus on sending humans to the moon and eventually to Mars. This endeavor presents new challenges that are critically different from the past experience with robotic missions to Mars. For example, the strict landing accuracy requirements for a manned space vehicle make it necessary to fly a controlled entry trajectory rather than a more robust ballistic entry trajectory used for some robotic missions. The large variations in Mars atmospheric properties make a controlled entry and a safe precision landing for manned missions a difficult engineering problem. Model reference adaptive control is a candidate solution for the Mars entry control problem. This type of controller has an adaptation mechanism that reduces tracking errors in the presence of uncertain parameters such as atmospheric density or vehicle properties. This thesis develops two different adaptive control systems for the Mars ellipsled, a vehicle which is much larger than those that carried robotic payloads to Mars in the past. A sample mission will have multiple ellipsleds arriving at Mars carrying an assortment of payloads. It is of critical importance that the vehicles land in close proximity to each other to best assure that the crew has manageable access to their payloads. The scope of this research encompasses the atmospheric flight of the ellipsled, starting at the entry interface point through the final parachute deployment. Tracking performance of an adaptive controller for prescribed entry trajectories in the pres¬ence of atmospheric and vehicle model uncertainties is shown here. Both adaptive controllers studied in this thesis demonstrate successful adaptation to uncertainties in the Martian atmosphere as well as errors in the vehicle properties. Based on these results, adaptive control is a potential option for controlling Mars entry vehicles.

In this thesis a model reference adaptive sliding mode control scheme is proposed for a class of linear time-invariant MIMO systems with unstructured and input, output uncertainties to solve the robust tracking problems. The designing of the proposed control scheme is divided into three steps. The first step is to design the sliding functions, the second step is to construct the estimators of the lumped perturbation. These estimators are able to estimate the derivatives of the tracking errors. The third step is to design the adaptive sliding mode controller. The proposed control scheme is designed without requiring the information of the upper bound of perturbations, and guarantee the stability of the controlled system. In fact the asymptotical stability can be achieved for some special cases. Finally, three numerical examples are presented to demonstrate the feasibility of the proposed control scheme.

The existing powertrain control system in Volvo CE's vehicles consists of various types of physical quantities that are controlled. One of them is the engine speed. The purpose of this thesis is to investigate whether there are other control strategies suitable for engine speed control, than the existing one. Currently, the existing control system requires re-calibration of the control parameters if hardware in the vehicle is replaced. The current controller is a gain-scheduled PID controller with control parameters that varies over the operating range. The aim has been to develop several different adaptive control strategies. Adaptive control methods are expected to adapt to the changes of the system that a replacement of hardware can bring. The performance and robustness of the developed controllers have been compared with the existing controller. The approach has been to implement the control strategies in Matlab/Simulink and simulate the process with existing engine software provided by Volvo CE. The next step was to test and verify the controllers in a real machine. The focus in this thesis work has been on the adaptive control strategies MRAC (Model-Reference Adaptive Control) and L1 Adaptive Control. In the MRAC structure the desired performance is specified in terms of a reference model that the real system is supposed to follow. Each time an error is generated, by comparing actual and desired output, a suitable algorithm is used in order to obtain the control signal that can minimize the error. In addition, modeling errors and disturbances are estimated so that the controller can compensate for these. L1 Adaptive Control is an extension of the MRAC structure. The difference is that before the control signal is fed to the real system, it is low-pass filtered. This is done in order to prevent feeding high frequencies into the system. The results show that adaptive control has potential to be used in engine speed control. Reference following and disturbance rejection is well handled and simulations have furthermore shown that the developed controllers can deal with changes in the hardware. One of the developed L1-controllers was implemented in a real machine with promising results. / Det existerande styrsystemet i Volvo CE:s maskiner har till uppgift att styra och reglera flera olika fysikaliska storheter. En av dessa storheter är motorvarvtalet. Syftet med detta examensarbete är att undersöka alternativa reglerstrategier som kan användas för att styra motorvarvtalet. Problemet idag är att det nuvarande styrsystemet kräver omkalibrering av regulatorparametrar när befintlig hårdvara i maskinen behöver ersättas på grund av föråldring eller slitage. Den nuvarande regulatorn är en parameterstyrd PID-regulator där regulatorparametrarna beror av aktuell arbetspunkt. Målet har varit att utveckla och prova flera olika adaptiva reglerstrategier. Dessa metoder förväntas kunna hantera förändringar och adaptera sig mot nya förhållanden och omständigheter som en hårdvaruförändring kan medföra. Prestanda och robusthet som de utvecklade regulatorerna erhåller har jämförts mot den existerande regulatorstrukturen. Tillvägagångssättet har varit att implementera reglerstrategierna i Matlab/Simulink samt simulera med tillhörande motormjukvara som Volvo CE tillhandahållit. I nästa fas skulle regulatorerna testas och verifieras i en riktig maskin. Fokuset har under detta examensarbete riktats mot de två adaptiva reglerstrategierna Model-Reference Adaptive Control (MRAC) och L1 Adaptive Control. MRAC-strukturen bygger på att specificera prestandan genom en referens-modell som det riktiga systemet skall följa. Varje gång en avvikelse uppstår så beräknas en lämplig styrsignal genom att beakta och försöka minimera skillnaden mellan det riktiga systemet och den önskade referens-modellen. Till detta modelleras och skattas störningar som regulatorn skall kompensera för. Tekniken inom L1 Adaptive Control är en utvidgning av MRAC. Önskat beteende specificeras även för denna regulatorstruktur men största skillnaden är att innan styrsignalen matas in till systemet så lågpassfiltreras den. Detta görs i förebyggande syfte för att inte släppa in onödigt höga frekvenser in i systemet. Resultaten visar att adaptiv reglering av motorvarvtalet har potential. Referensföljning och undertryckning av störningar hanteras väl och simuleringar har dessutom visat att de utvecklade regulatorerna kan hantera hårdvaruändringar. En av de utvecklade L1-regulatorerna implementerades i en riktig maskin och resultaten såg lovande ut.

Submitted by Marcos Samuel (msamjunior@gmail.com) on 2017-02-09T12:08:18Z No. of bitstreams: 1 Dissertação_Luis Carlos Moreno.pdf: 1851298 bytes, checksum: f9907551df010d1d88bf2f0c7996d153 (MD5) / Approved for entry into archive by Vanessa Reis (vanessa.jamile@ufba.br) on 2017-02-09T14:46:10Z (GMT) No. of bitstreams: 1 Dissertação_Luis Carlos Moreno.pdf: 1851298 bytes, checksum: f9907551df010d1d88bf2f0c7996d153 (MD5) / Made available in DSpace on 2017-02-09T14:46:10Z (GMT). No. of bitstreams: 1 Dissertação_Luis Carlos Moreno.pdf: 1851298 bytes, checksum: f9907551df010d1d88bf2f0c7996d153 (MD5) / Para modelar o problema, é usada a abordagem de Euler-Lagrange. A qual se aplicou a um kit experimental nomeado Ball-Balancer, de modo que pudera-se obter um conjunto de equações dinâmicas que representem, no espaço de estados, seu comportamento dinâmico completo. Algumas suposições foram feitas sobre a situação experimental para evitar assim uma excessiva complexidade e ter que lidar posteriormente com fortes não linearidades que tornarem ao modelo num caso de estúdio difícil de aplicar. Um esquema de controle adaptativo direto é aplicado a um kit Ball-Balancer, usado como planta não linear. A estabilidade do sistema em malha fechada, e o seu desempenho no rastreamento são discutidos sob o enfoque de Lyapunov, também a obtenção de uma lei de controle adequada, assumindo parâmetros conhecidos, posteriormente, utilizando a mesma metodologia foi obtido um conjunto de equações de adaptação de parâmetros que procuram precisão no seguimento do sinal, em presença de não linearidades desconhecidas. A aplicabilidade e funcionamento do algoritmo de controle desenvolvido é implementado por meio de simulação, utilizando Matlab e Simulink para executar o controlador não linear sob uma abordagem de Controle Adaptativo por Modelo de Referência (MRAC), obtendo alguns resultados satisfatórios, como a teoria prever.

Tailsitter UAVs (Unmanned Aerial Vehicles) are a type of VTOL (Vertical Take off and Landing) aircraft that combines the agility of a quadrotor drone with the endurance and speed of a fixed-wing aircraft. For this reason, they have become popular in a wide range of applications from tactical surveillance to parcel delivery. This thesis details a clean sheet design process for a tailsitter UAV that includes the dynamic modeling, control design, simulation, vehicle design, vehicle prototype fabrication, and testing of a tailsitter UAV. The goal of this process was to design a robust controller that is able to handle uncertainties in the system's parameters and external disturbances and subsequently can control the vehicle through the transition between vertical and horizontal flight regimes. It is evident in the literature that most researchers choose to model and control tailsitter UAVs using separate methods for the vertical and horizontal flight regimes and combine them into one control architecture. The novelty of this thesis is the use of a single dynamical model for all flight regimes and the robust control technique used. The control algorithm used for this vehicle is a MRAC (Model Reference Adaptive Control) law, which relies on reference models and gains that adapt according to the vehicle's response in all flight regimes. To validate this controller, numerical simulations in Matlab and flight tests were conducted. The combination of these validation methods confirms our adaptive controller's ability to control the transition between the vertical and horizontal flight regimes when faced with both parametric uncertainties and external disturbances. / Master of Science / Unmanned aircrafts have been a topic of constant research and development recently due to their wide range of applications and their ability to fly without directly involving pilots. More specifically, VTOL UAVs have the advantage of being able to take off without a runway while retaining the efficiency of a classical aircraft. A tailsitter UAV behaves as a traditional quadrotor drone when in its vertical configuration and can rotate to a horizontal configuration, where it takes advantage of its wings to fly as a conventional aircraft. Modeling the dynamics of the tailsitter UAV and designing an autopilot controller is the main focus of this thesis. An adaptive controller was chosen for the tailsitter UAV due to its ability to modify the gains of the system based on the behavior of the vehicle to adapt to the unknown vehicle properties. This controller was validated using both computer simulations and actual flight tests. It was found that the adaptive controller was able to successfully control the transition between the vertical and horizontal flight regimes despite the uncertainties in the parameters of the vehicle.

Although PID controllers work well on Miniature Air Vehicles (MAVs), they require tuning for each MAV. Also, they quickly lose performance in the presence of actuator failures or changes in the MAV dynamics. Adaptive control algorithms that self tune to each MAV and compensate for changes in the MAV during flight are explored. However, because the autopilots on MAVs are small, many of the adaptive control algorithms like those that employ least squares estimation may take too much code space, memory, and/or computing power. In this thesis we develop several Lyapunov-based model reference adaptive control (MRAC) schemes that are both simple and efficient with the MAV autopilot resources. Most notable are the L1 controllers that have all the benefits of traditional MRACs but have reduced high frequency content to the actuators. The schemes control both roll and pitch through aileron and elevator commands. Flight test results for the schemes are also compared.

Vertical Take-Off and Land (VTOL) Unmanned Air Vehicles (UAVs) possess several desirable characteristics, such as being able to hover and take-off or land in confined areas. One type of VTOL airframe, the tailsitter, has all of these advantages, as well as being able to fly in the more energy-efficient level flight mode. The tailsitter can track trajectories that successfully transition between hover and level flight modes. Three methods for performing transitions are described: a simple controller, a feedback linearization controller, and an adaptive controller. An autopilot navigational state machine with appropriate transitioning between level and hover waypoints is also presented. The simple controller is useful for performing a immediate transition. It is very quick to react and maintains altitude during the maneuver, but tracking is not performed in the lateral direction. The feedback linearization controller and adaptive controller both perform equally well at tracking transition trajectories in lateral and longitudinal directions, but the adaptive controller requires knowledge of far fewer parameters.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-07-08T21:04:13Z No. of bitstreams: 1 ThiagoFerreiraPaulo_DISSERT.pdf: 1256106 bytes, checksum: 42270ab696a6a5783b3e620be87e6519 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-07-12T18:19:22Z (GMT) No. of bitstreams: 1 ThiagoFerreiraPaulo_DISSERT.pdf: 1256106 bytes, checksum: 42270ab696a6a5783b3e620be87e6519 (MD5) / Made available in DSpace on 2016-07-12T18:19:22Z (GMT). No. of bitstreams: 1 ThiagoFerreiraPaulo_DISSERT.pdf: 1256106 bytes, checksum: 42270ab696a6a5783b3e620be87e6519 (MD5) Previous issue date: 2015-07-31 / O controle de sistemas MIMO (Multiple Input Multiple Output) ? muitas vezes realizado por v?rias malhas de controladores cl?ssicos que operam com restri??es e apresentam baixo desempenho. T?cnicas de controle adaptativo s?o uma alternativa interessante para aumentar o rendimento desses sistemas, como por exemplo os controladores MRAC (Model Reference Adaptive Control), que quando bem projetados, permitem que a din?mica da planta seja escolhida de maneira a seguir um modelo de refer?ncia. O presente trabalho apresenta uma estrat?gia de desacoplamento para um sistema MIMO de tr?s tanques acoplados e o projeto de um controlador MRAC para o mesmo.

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.