When sunlight illuminates a body, a tiny pressure is exerted upon its surface due to the photons impacting on it. Such a principle forms the basis of solar sailing, in which the solar radiation pressure is used to accelerate highly reflective lightweight structures called solar sails. Similarly, a laser-enhanced solar sail is a solar sail in which also an external laser beam pointed towards the sail is exploited to generate thrust. In this way an additional laser radiation pressure is exerted onto the sail, hence conferring higher propulsive and steering capabilities, and leading to an increased maneuverability of the sailcraft. The main purpose of this thesis project is to provide a model of the laser-enhanced solar sail dynamics and to establish the advantages of laser-enhanced solar sailing as compared to "traditional" solar sailing. The analysis has been pursued focusing on interplanetary missions and considering ideal sails, i.e. sails able to perfectly reflect the impinging radiation. Normally, for low-thrust interplanetary missions the propellant consumption and time of flight required for the transfers to take place play a crucial role. However, since solar sails do not exploit any propellant, the traditional and laser-enhanced sailcraft performances have been compared by analyzing their flight-time optimal trajectories, focusing on three different mission scenarios: a Mercury orbit rendezvous, Mars orbit rendezvous and Neptune flyby. These trajectories have been computed by taking advantage of an evolutionary neurocontrol optimizer, in which newly added functionalities have been implemented with the purpose of optimizing laser-enhanced solar sail trajectories. The trajectory analysis results have shown that, if laser-enhanced sailcraft are used instead of traditional sailcraft, flight time gains in the order of 8-11% can be achieved for the missions to Mercury and Mars orbits, while a smaller 2.5% gain is achieved for the flyby mission to Neptune.

With all major bodies within the Solar System explored by at least a single fly-by, modern-day missions are becoming increasingly more demanding, up to a point where classical chemical propulsion can no longer supply the required ∆V. Increasingly more is relied upon low-thrust propulsion, characterised by its (very) low thrust force; long continuous thrust arcs, often lasting months at a time; and high specific impulse. To even further increase the possible ∆V budget, thereby allowing more intricate missions, more payload, or a lower transfer time; use is made of low-thrust propulsion combined with gravity assists. With traditional low-thrust gravity assist optimisation tools heavily relying on astrodynamics and optimal control theory expertise, often requiring an initial guess and heavy modification for each new mission scenario; there is a need for a smart low-thrust gravity assist trajectory optimisation tool. Such a tool should be independent from an initial guess, optimise a trajectory from only a broad description of the mission, and be applicable to a wide variety of mission scenarios. It was the goal of this thesis to develop such a smart low-thrust gravity assist trajectory optimisation tool, which was found in extending the global low-thrust optimisation software package InTrance. InTrance tackles the problem from the novel perspective of artificial intelligence and machine learning using a method termed evolutionary neurocontrol (ENC), which combines biologically inspired artificial neural networks (ANNs) with evolutionary algorithms (EAs). The internal parameters of the ANN and initial conditions of each phase are optimised by the EA, which then serves as an agent; supplying the spacecraft with a steering strategy at each integration step. A novel tool capable of optimising the low-thrust gravity assist problem has been developed and has been shown to find more optimal results than available reference trajectories in select cases. Two prominent low-thrust gravity assist missions have been re-optimised: a double-asteroid rendezvous mission with an intermediate Mars gravity assist similar to the Dawn mission, and a low-thrust version of the New Horizons mission to Pluto with an intermediate Jupiter gravity assist. InTrance found a low-thrust New Horizons like trajectory which used 41% less propellant for a similar flight time as the actual mission, even though having a higher drymass and being launched with a lower C3. The results of the Dawn re-optimisation showed excellent agreement with the actual Dawn mission in terms of flight and dwell times, and used significantly less propellant. The efficiency increase due to the inclusion of the gravity assists has furthermore been investigated. The gravity assist at Jupiter in the New Horizons trajectory resulted in a decrease of 3.5% in flight time and over 75% in propellant saving. Dawn’s mission could be flown without a gravity assist w.r.t flight time and propellant usage, however, the inclusion resulted in an increase of 20% in dwell time at Vesta.