Abstract
In many space missions, spacecraft are required to have the ability to avoid various obstacles and finally reach the target point. In this paper, the path planning of spacecraft attitude maneuver under boundary constraints and pointing constraints is studied. The boundary constraints and orientation constraints are constructed as finite functions of path evaluation. From the point of view of optimal time and shortest path, the constrained attitude maneuver problem is reduced to optimal time and path solving problem. To address this problem, a metaheuristic maneuver path planning method is proposed (cross-mutation grey wolf algorithm (CMGWO)). In the CMGWO method, we use angular velocity and control torque coding to model attitude maneuver, which increases the difficulty of solving the problem. In order to deal with this problem, the grey wolf algorithm is used for mutation and evolution, so as to reduce the difficulty of solving the problem and shorten the convergence time. Finally, simulation analysis is carried out under different conditions, and the feasibility and effectiveness of the method are verified by numerical simulation.
Highlights
As a low-cost spacecraft, small satellites have the characteristics of light, agility, and large coverage
The optimization result is wonderful; the trajectory of the infrared telescope vector in the celestial coordinate system of the cross-mutation grey wolf optimizer is shown in Figure 4, where blue dots indicate obstacles
This paper describes and analyzes the boundary and pointing constraints of the spacecraft trajectory planning problem based on time and path optimization
Summary
As a low-cost spacecraft, small satellites have the characteristics of light, agility, and large coverage. The limitation of angular velocity and control torque will affect the attitude maneuver path [5, 6] Due to these complex constraints, time-optimized maneuvering path planning based on spacecraft guidance, navigation, and control systems is very challenging. We transform the satellite orbit planning problem into the optimization problem of finding the best time and shortest path and establish the spacecraft attitude maneuver model by angular velocity-time-control torque coding. A new algorithm OCS-GWO is proposed by the opposition-based chaotic grey wolf optimizer for global optimization task. The Cauchy grey wolf optimizer for continuous optimization problems proposes an improved classical GWO algorithm, which is named CauchyGWO. The grey wolf optimizer with enhanced leadership inspiration for global optimization problems proposes an improved leadership-based GWO, namely, GLF-GWO. By testing five benchmark functions, the results are compared with the traditional GWO algorithm to verify the superiority of the algorithm
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