No description available.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2002. / Includes bibliographical references (p. 188-189). / During the boost phase of ascent, winds have a significant impact on a launch vehicle's angle of attack, and can induce large structural loads on the vehicle. Traditional methods for mitigating these loads involve measuring the winds prior to launch and designing trajectories to minimize the vehicle angle of attack (a). The current balloon-based method of collecting wind field information produces wind profiles with significant uncertainty due to the inherent time delays associated with balloon measurement procedures. Managing the mission risk caused by these uncertain wind measurements has always been important to control system designers. This thesis will describe a novel approach to managing structural loads through the combination of a Light Detection and Ranging (LIDAR) wind sensor, and Model Predictive Control (MPC). LIDAR wind sensors can provide near real-time wind measurements, significantly reducing wind uncertainty at launch. MPC takes full advantage of this current wind information through a unique combination of proactive control, constraint integration and tuning flexibility. This thesis describes the development of two types of MPC controllers, as well as a baseline controller representative of current control methods used by industry. A complete description of Model Predictive Control theory and derivation of the necessary control matrices is included. The performance of each MPC controller is compared to that of the baseline controller for a wide range of wind profiles from both the Eastern and Western U.S. Test Ranges. Both MPC controllers are shown to provide reductions of greater than 50% in a, Qa and structural bending moments. In addition, the effects of wind measurement delays and uncertainty on the performance of each controller are investigated. / by Andrew Allen Martin. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1990. / Vita. / Includes bibliographical references (leaves 243-252). / by Daniel Michael Merfeld. / Ph.D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1996. / Includes bibliographical references (leaves 52-54). / by Martin Bowyer Graf. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1991. / Includes bibliographical references (leaves 119-121). / by Alexandra Maria Landsberg. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1990. / Includes bibliographical references (leaves 149-150). / by George Pappas. / M.S.

Thesis (M.S.)--Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics, 1986. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERO. / Bibliography: leaf 135. / by Craig Howard Smith. / M.S.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008. / Includes bibliographical references (leaves 145-153). / As unmanned aerial vehicles (UAVs) take on more prominent roles in aerial missions, it becomes necessary to increase the level of autonomy available to them within the mission planner. In order to complete realistic mission scenarios, the UAV must be capable of operating within a complex environment, which may include obstacles and other no-fly zones. Additionally, the UAV must be able to overcome environmental uncertainties such as modeling errors, external disturbances, and an incomplete situational awareness. By utilizing planners which can autonomously navigate within such environments, the cost-effectiveness of UAV missions can be dramatically improved.This thesis develops a UAV trajectory planner to efficiently identify and execute trajectories which are robust to a complex, uncertain environment. This planner, named Efficient RSBK, integrates previous mixed-integer linear programming (MILP) path planning algorithms with several implementation innovations to achieve provably robust on-line trajectory optimization. Using the proposed innovations, the planner is able to design intelligent long-term plans using a minimal number of decision variables. The effectiveness of this planner is demonstrated with both simulation results and flight experiments on a quadrotor testbed.Two major components of the Efficient RSBK framework are the robust model predictive control (RMPC) scheme and the low-level planner. This thesis develops a generalized framework to investigate RMPC affine feedback policies on the disturbance, identify relative strengths and weaknesses, and assess suitability for the UAV trajectory planning problem. A simple example demonstrates that even with a conventional problem setup, the closed-loop performance may not always improve with additional decision variables, despite the resulting increase in computational complexity. A compatible low-level troller is also introduced which significantly improves trajectory-following accuracy, as demonstrated by additional flight experiments. / by Brandon Luders. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2009. / Includes bibliographical references (p. 91-94). / As unmanned aerial vehicles (UAVs) become more involved in challenging mission objectives, the need for agility controlled flight becomes more of a necessity. The ability to navigate through constrained environments as well as quickly maneuver to each mission target is essential. Currently, individual vehicles are developed with a particular mission objective, whether it be persistent surveillance or fly-by reconnaissance. Fixed-wing vehicles with a high thrust-to-weight ratio are capable of performing maneuvers such as take-off or perch style landing and switch between hover and conventional flight modes. Agile flight controllers enable a single vehicle to achieve multiple mission objectives. By utilizing the knowledge of the flight dynamics through all flight regimes, nonlinear controllers can be developed that control the aircraft in a single design. This thesis develops a full six-degree-of-freedom model for a fixed-wing propeller-driven aircraft along with methods of control through non conventional flight regimes. In particular, these controllers focus on transitioning into and out of hover to level flight modes. This maneuver poses hardships for conventional linear control architectures because these flights involve regions of the post-stall regime, which is highly nonlinear due to separation of flow over the lifting surfaces. Using Lyapunov back stepping control stability theory as well as quaternion-based control methods, control strategies are developed that stabilize the aircraft through these flight regimes without the need to switch control schemes. The effectiveness of each control strategy is demonstrated in both simulation and flight experiments. / by Frantisek Michal Sobolic. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1992. / Includes bibliographical references (leaves 214-219). / by Dava Jean Newman. / Ph.D.