In recent years, NASA has indicated a desire to return humans to the moon. With NASA planning manned missions within the next couple of decades, the concept development for these lunar vehicles has begun. The guidance, navigation, and control (GN&C) computer programs that will perform the function of safely landing a spacecraft on the moon are part of that development. The lunar descent guidance algorithm takes the horizontally oriented spacecraft from orbital speeds hundreds of kilometers from the desired landing point to the landing point at an almost vertical orientation and very low speed. Existing lunar descent GN&C algorithms date back to the Apollo era with little work available for implementation since then. Though these algorithms met the criteria of the 1960's, they are cumbersome today. At the basis of the lunar descent phase are two elements: the targeting, which generates a reference trajectory, and the real-time guidance, which forces the spacecraft to fly that trajectory. The Apollo algorithm utilizes a complex, iterative, numerical optimization scheme for developing the reference trajectory. The real-time guidance utilizes this reference trajectory in the form of a quartic rather than a more general format to force the real-time trajectory errors to converge to zero; however, there exist no guarantees under any conditions for this convergence. The proposed algorithm implements a purely analytical targeting algorithm used to generate two-dimensional trajectories "on-the-fly" or to retarget the spacecraft to another landing site altogether. It is based on the analytical solutions to the equations for speed, downrange, and altitude as a function of flight path angle and assumes two constant thrust acceleration curves. The proposed real-time guidance algorithm has at its basis the three-dimensional non-linear equations of motion and a control law that is proven to converge under certain conditions through Lyapunov analysis to a reference trajectory formatted as a function of downrange, altitude, speed, and flight path angle. The two elements of the guidance algorithm are joined in Monte Carlo analysis to prove their robustness to initial state dispersions and mass and thrust errors. The robustness of the retargeting algorithm is also demonstrated.

No description available.

No description available.

Erratum pasted on front fly leaf. / Bibliography: leaves 204-214. / xxi, 214 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This thesis investigates a novel guidance law dubbed "observable proportional navigation". Two distinct forms of this guidance law are considered, based on the nature of the associated noise and state estimator. Closed-form solutions are given and necessary limits on the co-efficient of observability are determined. Both forms of the new law are applied to a two-dimensional missile-target bearing-only-measurement problem. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1995

Bibliography: leaves 220-229. / xxiv, 229 leaves : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Investigates alternative reusable launch vehicle design concepts and develops a robust guidance strategy for use on the ascent and flyback phases of flight. The first concept vehicle uses air breathing engines to perform a powered return flight to the launch site; the second employs only aerodynamic forces to achieve flyback, returning unpowered. Software simulation shows that a powered return flight delivers more payload than an unpowered return flight. The guidance strategy developed is a numerical guidance system robust enough for use in real time and works by integrating the current state, along the trajectory, to the final state of the vehicle. It then compares the achieved final state to the required target state and calculates the target condition error. A parameterised non-linear optimisation technique is then used to determine the new values of the optimisation parameters required to steer the vehicle from its current position and velocity to the desired position and velocity. / Thesis (Ph.D.)--University of Adelaide, School of Mechanical Engineering, 2003

Thesis (MScIng)--University of Stellenbosch, 2006. / Bibliography. Also available via the Internet.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 111-114).

Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 88 pages. Includes vita. Includes bibliographical references.

Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 42 pages. Includes vita. Includes bibliographical references.

Thesis (M.S.)--University of Florida, 2004. / Title from title page of source document. Document formatted into pages; contains 44 pages. Includes vita. Includes bibliographical references.