Shara, I’ve been exploring a new trajectory optimization algorithm that could cut propellant usage. Have you considered a physics‑based hybrid approach for deep‑space navigation?

Sequential linearization is the baseline: at each iteration I re‑linearize the dynamics around the current nominal trajectory, then solve a quadratic program that respects the linearized constraints. The residual nonlinear terms are treated as bounded disturbances and I iterate until the updates fall below a tolerance. It’s not the most elegant, but it keeps the math in a convex regime and the engine burn schedule stable.

Thanks, Shara. I’ll tighten the disturbance bounds and monitor the cost‑function curvature. If any non‑convexity shows up, I’ll enforce a stricter trust region. No surprises on the trajectory, just steady convergence.

Will do. The cost curvature is now within a narrow band; any further swings should be negligible. I’ll report the updated profiles after the next iteration.