Low-thrust fuel-optimal transfer orbit guidance using SCP and SQP

Optimization techniques for spacecraft orbital transfers typically utilize discrete velocity impulses as their optimization parameters. While these methods are effective for short-term, high-thrust chemical propulsion systems, they are not ideal for long-term, low-thrust electric propulsion systems. To address the challenge of autonomous guidance for continuous thrust orbital transfers, this paper presents a guidance model that uses engine thrust as the optimization variable. It also introduces a hybrid optimization approach that combines sequential convex programming (SCP) and sequential quadratic programming (SQP) to facilitate autonomous maneuver control. The hybrid method initially employs SCP to tackle the guidance problem, leveraging its global optimality and rapid convergence to determine the optimized thrust sequence. The outcomes from SCP serve as starting points for SQP, which refines the solution through its local search capabilities, enhancing accuracy. Numerical simulations indicate that this approach is over 20 times faster than using SQP alone and improves insertion position accuracy by nearly 190 times compared to SCP alone, with velocity accuracy increasing by four orders of magnitude. The SCP-SQP-based guidance method demonstrates high reliability and significant potential for autonomous spacecraft guidance applications. Reason: Improved clarity, readability, and technical accuracy while maintaining the original meaning.