Application of an A* node search to plume-fuel optimization of spacecraft trajectories

Abstract

Spacecraft proximity operations are complicated by the fact that exhaust plume impingement h m the reaction control jets of space vehicles can cause structural damage, contamination of sensitive arrays and instruments, or attitude misalignment during docking. An A* node search is used to find plume-fuel optimal trajectories through a discretized six dimensional attitudetranslation space. plume cost function which approximates jet plume iso-pressure envelopes is presented. The function is then applied to find relative costs for predictable firings and unpredictable firings. Trajectory altering firings are calculated by running the spacecraft jet selection algorithm and summing the cost contribution from each jet fired. function is defined and integrated to detennine the potential for deadbanding impingement along candidate trajectories. Plume costs are weighed against fuel costs in finding the optimal solution. A* convergence speed is improved by solving approach trajectory problems in reverse time. Results are obtained on a high fidelity Space Shuttle/Space Station simulation. Trajectory following is accomplished by a six degree of freedom autopilot. Trajectories planned with, and without, plume costs are compared in terms of total force applied to the target structure. Copyright Q 1995 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. The occurrence and effect of jet plume impingement can be reduced by planning approach trajectories with plume effects considered. Trajectory selection impacts plume impingement in two ways. First, the final approach trajectory determines the geometric positioning of jet groups relative to target structures, thereby determining which jet groups are likely to cause damage or misalignment. Second, the trajectory choice determines how the vehicle is affected by orbital mechanics. Thus, the commanded trajectory determines which jets will point at which target structure, and influences whether or not they will be needed. An intelligent trajectory planner can reduce plume costs by searching for trajectories which minimize the potential for impingement. Such a planner should consider both translation and attitude since together these determine the degree of plume impingement for a given jet firing. Several studies have focused on various aspects of trajectory planning for proximity operations. Bergmann et a1 applied a gradient descent technique to trajectory optimization over fuel costs1. The principles of artificial potential fields have been applied to proximity trajectory generation2. Two recent studies used the A* (pronounced A star) node search technique to find fuel optimal trajectories3s4. These works provide the basis for some of the A* strategies used here. Much effort has gone into accurate modeling of reaction jet plumes and their effects on target structures.5,6*7 At least one study considered dynamic plume avoidance that is, modifying the jet selection scheme to prevent or reduce plume impingement* for a given trajectory. Other work has modeled the plume as a truncated cone and applied a$ollision detection algorithm9.