A quadrotor is a type of small unmanned aerial vehicle (UAV) with four rotors. Various control techniques have been successfully applied to the quadrotor. In this thesis, two control methods, including linear quadratic regulator (LQR) and H2-optimal control, are applied to the autonomous navigation and control of a quadorotor named QBall-X4 that is developed by Quanser. The continuous-time dynamic model is established using the Euler-Lagrange approach. Due to the nonlinearities in the quadrotor dynamics, we propose a simplified linear model, which is further used for the controller design in this thesis. According to the simplified quadrotor dynamics, we design an LQR controller to regulate the quadrotor system from its initial position to the desired position. The effectiveness of the controller is verified by simulation studies. However, the LQR control system is operated in the nominal model, and it can not present guaranteed performance when system uncertainties exist. The main emphasis is placed on designing an H2-optimal controller that minimizes the H2-norm of the transfer function. The solution is obtained by using the state-space approach and linear matrix inequality (LMI) method, respectively. In contrast to LQR control method, which is normally applied to a system with no disturbance, the H2-optimal controller takes the form of an observer together with a state feedback control gain to deal with the system uncertainties and disturbances. The simulation results and experimental study verify that the proposed H2-optimal controller is an effective option for the quadrotor with the attendance of uncertainties and disturbances. / Graduate

Forests represent one of the biggest terrestrial ecosystems of Earth, that can produce important raw renewable materials such as wood with the help of sun, air and water. To efficiently extract these raw materials, the tree harvesting process is highly mechanized in developed countries, meaning that advanced forestry machines are continuously used to fell, to process and to transport the logs and biomass obtained from the forests. However, working with these machines is demanding both mentally and physically, which are known factors to negatively affect operator productivity. Mental fatigue is mostly due to the manual operation of the on-board knuckleboom crane, which requires advanced cognitive work with two joystick levers, while the most serious physical strains arise from cabin vibrations. These vibrations are generated from knuckleboom crane vibrations as a result of aggressive manual operation. To enhance operator workload, well-being, and to increase productivity of the logging process, semi-automation functions are suggested, which are supervised automatic executions of specific work elements. Some of the related issues are addressed in the current thesis. Therefore, the content is divided into: (1) the design and development of a semi-automation function focused only on the base joint actuator (slewing actuator) of a knuckleboom crane, and (2) active vibration damping solutions to treat crane structure vibrations induced by the main lift cylinder (inner boom actuator). The considered reference machine is a downsized knuckleboom crane of a forwarder machine, which is used to pick up log assortments from a harvesting site. The proposed semi-automation function presented in the first part could be beneficial for operators to use during log loading/unloading scenarios. It consists from a closed-loop position control architecture, to which smooth reference slewing trajectories are provided by a trajectory planner that is automated via operator commands. The used trajectory generation algorithms are taken from conventional robotics and adapted to semi-automation context with proposed modifications that can be customizable by operators. Further, the proposed active vibration damping solutions are aimed to reduce vibrations of the knuckleboom crane excited by the inner boom actuator due to aggressive manual commands. First, a popular input shaping control technique combined with a practical switching logic was investigated to deal with the excited payload oscillations. This technique proved to be useful with a fixed crane pose, however it did not provide much robustness in terms of different link configurations. To tackle this problem an H2-optimal controller is developed, which is active in the pressure feedback-loop and its solely purpose is to damp the same payload oscillations. During the design process, operator commands are treated and explained from input disturbance viewpoint. All of the hypothesis throughout this thesis were verified with extensive experimental studies using the reference machine.