The minimum-energy fixed-time rest-to-rest reorientation of an asymmetric rigid-body spacecraft is investigated. The problem is first formulated as a non-convex optimal control problem using a quaternion based dynamic model. Past attempts at solving this problem either sacrifice fidelity to solve analytically or require computationally intensive nonlinear programming (NLP) solvers to tackle the original problem. However, through discretization and constraint implementation, the original optimal control problem is transformed into a sequential convex programming (SCP) problem. Additionally, a simple line search method is introduced to aid in the convergent process of the SCP method. Through numerical demonstrations, the SCP approach has been shown to converge to the minimum-energy optimal solution, even with trivial initial trajectories. The solutions are validated through a comparison with an NLP-based solver, GPOPS. Additionally, line search (LS) has been shown to aid convergence of SCP by decreasing the number of iterations by a significant amount. This introduces a novel approach to solve the minimum-energy fixed-time rest-to-rest reorientation in real time.
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