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Thesis (MScIng)--University of Stellenbosch, 2007. / Bibliography.

Thesis ( M.S.)--Air Force Institute of Technology, 2007. / AFIT/GAE/ENY/07-M05. Title from title page of PDF document (viewed on: Nov. 27, 2007). "March 2007." Includes bibliographical references (leaves 79-80).

Thesis (MIng)--University of Stellenbosch, 2004. / Includes bibliographical references. Also available via the Internet.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 74-76).

The problem of aircraft control allocation is that of finding a combination of control positions that cause the resulting aircraft moments to most closely satisfy a given desired moment vector. The problem is easily solved for the case of an aircraft having three control surfaces, each of which primarily imparts moments in each of the three aircraft axes. In this simple case, the solution to the control allocation problem is uniquely determined. However, many current and future aircraft designs employ a larger set of control effectors, resulting in a control redundancy in the sense that more than one combination of control positions can produce the same desired moment. When taking into account both the position and rate constraints of the control effectors, the problem is significantly more complex. Constrained moment-rate control allocation guarantees a control solution that can achieve every possible moment that is physically realizable by the aircraft. Addressed here is the real-time performance of moment-rate constrained control allocation as tested on a desktop simulation. Issues that were deemed interesting or potentially problematic in earlier batch simulation, such as control chattering due to restoring and apparent control wind-up, are investigated and an evaluation is made of the overall feasibility of these algorithms. The purpose of the research is to confirm that the results obtained from batch simulation testing are also valid using maneuvers representative of real-time flight and representative simulation frame sizes, and to uncover potential problems not observed in batch simulation. NOTE: An updated copy of this ETD was added on 05/29/2013. / Master of Science

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This thesis reviews the applications of Kalman filtering estimation to the problem of target tracking. Both linear and nonlinear forms of Kalman filter are reviewed and models of target manoeuvre discussed. Manoeuvre adaptation schemes are examined to detect the onset and completion of manoeuvres. Target manoeuvre coordinates are also examined and a new target model proposed which significantly improves tracking performance. The new model includes turn rate estimation. The real-time implementation of tracking Kalman filters is also studied both for a simple processor and a multiple processor architecture. Tracking algorithms are coded in Parallel C and evaluated for speed and efficiency

In the last decades, the quadrotor has been used in many areas, and deigning an effective flight control algorithm for the quadrotor has attracted great interests in both control and robotics communities. This thesis focuses on the flight control of the quadrotor by using different methods: The extend Kalman filter (EKF) based linear quadratic regulator (LQR) method and learning-based model predictive control (LBMPC) method. Chapter 4 investigates the flight control of a quadrotor subject to the model uncertainties and external disturbances. We propose a LQR based tracking algorithm. However, the designed LQR controller is hard to be implemented because of the existing noises in the measured states. A modified EKF is then designed for the online estimation of the position, velocity and motor dynamics by using the measured outputs. From the experimental testing results, it is shown that the proposed EKF-based LQR control method solves the tracking problem of the quadrotor with less tracking errors than only using the LQR method. In Chapter 5, the tracking control problem of the quadrotor subject to external disturbances and physical constraints is studied. A model predictive control (MPC) based algorithm is proposed. To reduce the computational load, a modified prior barrier interior-point method is used to solve the quadratic programming (QP) problem. Nevertheless, the achievable flight performance by using the standard MPC algorithm is affected by external disturbances. A LBMPC algorithm is proposed for the disturbance rejection. From the simulation results, it is shown that using the proposed LBMPC algorithm have less tracking errors than applying the standard MPC algorithm. / Graduate

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