17 papers · 1 filter
Transcription-Induced Failure Modes in 6-DOF Rocket Landing Trajectory Optimization
Prayag Sharma, Jonathan Y. M. Goh, Behçet AçıkmeÅe +1
Solving optimal control problems via large-scale NLP solvers depends on discretizing continuous dynamics. Yet, this transcription step hides critical vulnerabilities-most notably t…
A Sequential Operator-Splitting Framework for Exploration of Nonconvex Trajectory Optimization Solution Spaces
Justin Ganiban, Natalia Pavlasek, Behcet Acikmese
Trajectory optimization methods provide an efficient and reliable means of computing feasible trajectories in nonconvex solution spaces. However, a well-known limitation of these a…
Funnel Synthesis via LMI Copositivity Conditions for Nonlinear Systems
Taewan Kim, Behçet AçıkmeÅe
Funnel synthesis refers to a procedure for synthesizing a time-varying controlled invariant set and an associated control law around a nominal trajectory. The computation of the fu…
Six-Degree-of-Freedom Aircraft Landing Trajectory Planning with Runway Alignment
Taewan Kim, Abhinav G. Kamath, Niyousha Rahimi +3
This paper presents a numerical optimization algorithm for generating approach and landing trajectories for a six-degree-of-freedom (6-DoF) aircraft. We improve on the existing res…
Discrete lossless convexification for pointing constraints
Dayou Luo, Fabio Spada, Behçet AçıkmeÅe
Discrete Lossless Convexification (DLCvx) formulates a convex relaxation for a specific class of discrete-time non-convex optimal control problems. It establishes sufficient condit…
Revisiting Lossless Convexification: Theoretical Guarantees for Discrete-time Optimal Control Problems
Dayou Luo, Kazuya Echigo, Behçet AçıkmeÅe
Lossless Convexification (LCvx) is a modeling approach that transforms a class of nonconvex optimal control problems, where nonconvexity primarily arises from control constraints,…