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20242026
most citedDeep Neural Network-Based High-Precision Identification of Weak Stability Boundary Structures

5 citations · 5 across the 11 of their papers we have counts for

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6 papers · 1 filter

math.OC2026

System Level Synthesis for Fast Chance-Constrained Post-Fault Ascent Replanning under Persistent Propulsion Uncertainty

Dai Shen, Chen Yang, Lin Cheng +3

A nonfatal propulsion fault can invalidate the nominal ascent trajectory while leaving sufficient vehicle capability to reach the original orbit or a degraded target. Deterministic…

math.OC2026

Condensed PIPG Sequential Convex Optimization for Reusable-Rocket Powered Landing with Strong Aerodynamics

Wenbo Li, Linwei Li, Ziqi Xu +1

Reusable-rocket powered landing under strong aerodynamics couples variable mass, free final time, and bounded aerodynamic controls through nonlinear velocity-frame dynamics. This p…

math.OC2026

Dual-Thrust Switching Analytical Guidance Algorithm for Powered Landing with Attitude Smoothness Optimization

Wenbo Li, Dai Shen, Shengping Gong

Traditional numerical guidance methods for powered landing of reusable rockets are typically constrained by high computational complexity and inadequate real-time performance. More…

math.OC2026

Submillisecond Sequential Convex Optimization for Powered Landing via Dynamics Condensation and xPIPG

Wenbo Li, Ziqi Xu, Dai Shen +1

Powered landing with variable mass, free final time, and quadratic aerodynamic drag requires the repeated solution of local convex subproblems, whose main online cost lies in the l…

math.OC2026

Microsecond-Class Powered-Descent Optimization via Exact Condensation and Strong Convex Regularization

Wenbo Li, Ziqi Xu, Dai Shen +1

Fuel-dominant powered descent can be written as a convex program, but the usual full-state epigraph formulation still carries many state variables, fuel epigraph variables, and dyn…

math.OC2025

Parameter Optimization in Trajectory Planning via Differentiable Convex Programming

Ziqi Xu, Lin Cheng, Di Wu +1

Sequential convex programming has been established as an effective framework for solving nonconvex trajectory planning problems. However, its performance is highly sensitive to pro…