No description available.

In flying robots, stability control is often very sensitive to the actuator performances, and the software module performing the controller, is usually subjected to a long and difficult tuning phase strongly dependent on the specific actuator used. The actuators are often electric motors equipped with propellers. The motor and propeller combination performs differently for every choice of components adopted, even if they are provided by the same vendor with the same part family. The project aims to develop an intelligent actuator module for flying robots composed by a BLDC motor and a propeller, which is invariant to the specific motor and propeller adopted. By gathering the force data of the four used on a quadrocopter, the force and control signal relation could be defined and stored into the program memory of the control board. A battery monitor and a Force-PWM controller was implemented such that it takes force as input and outputs the desired PWM-signal. Tests were made on a prototype of Iqarus quadrocopter and by mounting it with ropes to the floor, it was tested on the lift-off phase. The experiment showed theoretical and practical results, which concludes that the quadrocopter maintained the ability to lift right upwards without any remaining control, assuming proper weight balance of the quadrocopter. / Inom flygande robotar, är stabilitet kontrollen oerhört känsligt till styrdonets prestation, och mjukvaru modulen som utför kontrollen, är ofta förknippad med en lång och problematisk justerings fas starkt beroende av de enskilda styrdonen. Styrdonen är ofta elektriska motorer med propeller. Motor och propeller kombinationen uppträder olika för varje val av komponent, även om komponenterna är försedda från samma återförsäljare och modell. Syftet med detta projekt är att utveckla en intelligent styrdons modul för flygande robotar, omfattad av en BLDC motor och propeller, som blir oberoende av den särskilda motor och propeller kombination som används. Genom att samla kraft data för de fyra styrdonen som används på en quadrocopter, kunde relationen mellan kraft och kontroll signal bli definierad och lagrad i program minnet för kontrol kortet. En batteri monitor och en Kraft-PWM kontroller implementerades, vilket tar kraft data som ingång och skickar ut motsvarande PWM-signal som utgång. Tester var gjorda med en prototyp av Iqarus quadrocopter och genom att binda fast den med rep till golvet, testades den för upplyfts fasen. Experimenten visade teoretiska och praktiska resultat, vilket visar att quadrocoptern bevarade förmågan att lyfta rakt uppåt utan någon övrig kontroll, förutsatt ordentlig vikt balans av quadrocoptern. / <p>Hejsan,</p><p>Detta ar den nya versionen, som ska ersatta den gamla versionen som blev uppladdad 6/11-13.</p><p>Tack,</p><p></p><p>Mvh</p><p>Amil Lafih</p>

The objective of this thesis is to investigate how the onboard battery of a quadcopter can be charged through manual rotation of its motors, while understanding the resulting aerodynamical forces acting on the rotors during hover, as well as considering the changes in thrust capabilities when the electronic and structural design are altered. A theoretical approach using the momentum theory will present a general understanding of rotor performance whilst describing the correlation between rotor parameters, thrust and mechanical power. Furthermore, the idea of using the motors as generators are put under study to investigate their electrical output and utilize them to recharge the battery. This is done using the counter electromotive force equation, and a sequence of other equations that will present numerical data of actual manual work converted into electrical power. Resulting in the required time to manually recharge the quadcopter subsequently sustaining hover flight for three minutes. It is concluded in this report that manual recharging of the battery using the motors as generators is possible, as well as maintaining its flying ability in case of added weight. Although not deemed practical in commercial use, it is a new methodology with the intention to develop a sustainable quadcopter further expanding its practical applications in both aviation industry and human aid.

This work deals with physical laws affecting behavior of a quadcopter as a mobile robot. It describes methods of controlling movements and stability. The result of the theoretical analysis is creation of simulation model. Moreover it depicts practical software developement of a real machine controller unit with its own conclusion, comparison between simulation and practical experiments and the workflow of the physical system construction.

This thesis deals with the design and theoretical description of the hybrid control system for quadrocopter. First, a mathematical model is presented, sensors needed for development and their principles. This work shows the system architecture design and scheme of communication channels between the blocks. Implementation section discusses specific uses of computing nodes/sensors and their settings. In this thesis there are illustrated messages sent between computing nodes and the control loop machine. It also describes how to test the sensors, measurement results and techniques for improvement.

Testing software-intensive systems can be challenging, especially when safety requirements are involved. Property-Based Testing (PBT) is a software testing technique where properties about software are specified and thousands of test cases with a wide range of inputs are automatically generated based on these properties. PBT does not formally prove that the software fulfils its specification, but it is an efficient way to identify deviations from the specification. Safety-critical systems that must be able to deal with faults, without causing damage or injuries, are often tested using Fault Injection (FI) at several abstraction levels. The purpose of FI is to inject faults into a system in order to exercise and evaluate fault handling mechanisms. The aim of this thesis is to investigate how knowledge and techniques from the areas of FI and PBT can be used together to test functional and safety requirements simultaneously. We have developed a FI tool named FaultCheck that enables PBT tools to use common FI-techniques directly on source code. In order to evaluate and demonstrate our approach, we have applied our tool FaultCheck together with the commercially available PBT tool QuickCheck on a simple and on a complex system. The simple system is the AUTOSAR End-to-End (E2E) library and the complex system is a quadcopter simulator that we developed ourselves. The quadcopter simulator is based on a hardware quadcopter platform that we also developed, and the fault models that we inject into the simulator using FaultCheck are derived from the hardware quadcopter platform. We were able to efficiently apply FaultCheck together with QuickCheck on both the E2E library and the quadcopter simulator, which gives us confidence that FI together with PBT can be used to test and evaluate a wide range of simple and complex safety-critical software. / <p>This research has been funded through the PROWESS EU project (Grant agreement no: 317820), the KARYON EU project (Grant agreement no: 288195) and through EISIGS (grants from the Knowledge Foundation).</p> / PROWESS / KARYON

No description available.

[pt] Neste trabalho, aborda-se a modelagem e controle de um quadricóptero para navegação autônoma em ambientes agrícolas. Os modelos cinemático e dinâmico do veículo aéreo são computados a partir do formalismo de Newton-Euler, incluindo efeitos aerodinâmicos e características das hélices. O sistema de movimento do quadricóptero pode ser dividido em dois subsistemas, um translacional e outro rotacional, responsáveis pelo controle de posição nos eixos x, y, z, and atitude do veículo no espaço Cartesiano. A primeira abordagem de controle é linear, se presenta dois controladores, um controlador proporcional-derivativo (PD) e o adaptativo baseado no espaço de estados. A segunda abordagem é não-linear e baseada em um controlador adaptativo a fim de lidar com a presença de incertezas nos parâmetros do sistema. Simulações numéricas são executadas em Matlab para ilustrar o desempenho e a viabilidade da metodologia de controle proposta. Simulações computacionais 3D são executadas em Gazebo para verificar a navegação autônoma em um campo agrícola. / [en] In this work, we address the modeling and control design of a quadrotor for autonomous navigation in agricultural environments. The kinematic and dynamic models of the aerial vehicle are derived following the Newton-Euler formalism. The motion system of the quadrotor can be split into two subsystems, that is, translational and rotational subsystems, responsible for controlling the position along the longitudinal, transverse and vertical axes of the Cartesian space as well as its orientation about the corresponding axes. The first linear control approach is based on the proportional-derivative (PD) controller, whereas the second nonlinear control approach is based on an adaptive controller in order to deal with the presence of uncertainties in the system parameters. Numerical simulations are carried out in Matlab to illustrate the performance and feasibility of the proposed control methodology. Gazebo was used to perform the 3D simulations for verifying autonomous navigation in agricultural fields.

[pt] Quadricópteros vêm sendo o objeto de estudo de inúmeras pesquisas ao redor do mundo. Diversas técnicas de controle já foram desenvolvidas, cada uma com seus prós e contras, objetivando o aprimoramento do desempenho destes veículos aéreos na consecução de tarefas específicas. Este trabalho foca na comparação de características de desempenho de técnicas de controle aplicadas a quadricópteros. Este trabalho mostra o projeto de controles modernos aplicados à quadricópteros apresentando tais técnicas, iniciando com a realimentação de estados com polos dominantes, passando pelo controle Linear Quadratic Regulator (LQR). Por sua vez, visando otimizar o desempenho das técnicas de controle aqui estudadas, foram aplicadas técnicas de inteligência computacional para resolver um problema de otimização do LQR e para auxiliar no controle de forças dos rotores. Apresenta-se o projeto de um controle PID, que será usado como referência para as demais técnicas analisadas. O controle por realimentação de estados citado anteriormente obteve bons resultados. O tempo de assentamento foi o menor para o eixo Z, overshoots e o erro em regime permanente, os menores para os eixos X e Y. O controlador Fuzzy conseguiu fazer seu papel auxiliando a movimentação do quadricóptero. O GA otimizou o tempo de assentamento do LQR. Esse controle conseguiu alcançar os menores tempos de assentamento para os eixos X e Y, sendo mais rápido que a configuração original do LQR, escolhida por heurísticas. Com esse trabalho foi possível notar que os controladores modernos, realimentação de estado e LQR, tem um desempenho melhor que o controle PID de referência. / [en] Quadcopters are researched all over the world. A lot of techniques had been developed and many others a blistering, each one with their pros and cons. The focus of this work is the comparison between the performance of some techniques most used in quadcopters, qualifying these techniques. This work shows the designing process of a quadcopter controllers, starting with state feedback with dominant poles and going to the Linear Quadratic Regulator controller. Focusing on optimizing the performance of those control strategies, computational techniques were used to solve an LQR optimization problem and to help choose the best inputs for the rotors. This work presents a PID controller that will be used as a reference for comparison. The state feedback controller with the Fuzzy position control performed very well, being the fastest one to settle on the Z axis, having the least overshoots and the lowest steadystate errors for the X and Y axes. The Fuzzy controller did what was supposed to do, smoothing and enabling a precise movement for the quadcopter. The GA also did what was supposed to do and improved the settling time for the LQR controller. It showed that it was a nice way to tune the Q and R matrixes, allowing the controller to be the fastest one to settle in the X and Y axes. As a result of this work, the modern control techniques, state feedback and LQR, performance better than the classic PID controller, used as reference.

Optimal control for multicopters is difficult in part due to the low processing power available, and the instability inherent to multicopters. Deep imitation learning is a method for approximating an expert control policy with a neural network, and has the potential of improving control for multicopters. We investigate the performance and reliability of deep imitation learning with trajectory optimization as the expert policy by first defining a dynamics model for multicopters and applying a trajectory optimization algorithm to it. Our investigation shows that network architecture plays an important role in the characteristics of both the learning process and the resulting control policy, and that in particular trajectory optimization can be leveraged to improve convergence times for imitation learning. Finally, we identify some limitations and future areas of study and development for the technology. / Optimal kontroll för multikoptrar är ett svårt problem delvis på grund av den vanligtvis låga processorkraft som styrdatorn har, samt att multikoptrar är synnerligen instabila system. Djup imitationsinlärning är en metod där en beräkningstung expert approximeras med ett neuralt nätverk, och gör det därigenom möjligt att köra dessa tunga experter som realtidskontroll för multikoptrar. I detta arbete undersöks prestandan och pålitligheten hos djup imitationsinlärning med banoptimering som expert genom att först definiera en dynamisk modell för multikoptrar, sedan applicera en välkänd banoptimeringsmetod på denna modell, och till sist approximera denna expert med imitationsinlärning. Vår undersökning visar att nätverksarkitekturen spelar en avgörande roll för karakteristiken hos både inlärningsprocessens konvergenstid, såväl som den resulterande kontrollpolicyn, och att särskilt banoptimering kan nyttjas för att förbättra konvergenstiden hos imitationsinlärningen. Till sist påpekar vi några begränsningar hos metoden och identifierar särskilt intressanta områden för framtida studier.