14 citations · 15 across the 4 of their papers we have counts for
6 papers
Fast Monte Carlo Analysis for 6-DoF Powered-Descent Guidance via GPU-Accelerated Sequential Convex Programming
Govind M. Chari, Abhinav G. Kamath, Purnanand Elango +1
We introduce a GPU-accelerated Monte Carlo framework for nonconvex, free-final-time trajectory optimization problems. This framework makes use of the prox-linear method, which belo…
Successive Convexification for Nonlinear Model Predictive Control with Continuous-Time Constraint Satisfaction
Samet Uzun, Purnanand Elango, Abhinav G. Kamath +2
We propose a nonlinear model predictive control (NMPC) framework based on a direct optimal control method that ensures continuous-time constraint satisfaction and accurate evaluati…
Successive Convexification for Trajectory Optimization with Continuous-Time Constraint Satisfaction
Purnanand Elango, Dayou Luo, Abhinav G. Kamath +3
We present successive convexification, a real-time-capable solution method for nonconvex trajectory optimization, with continuous-time constraint satisfaction and guaranteed conver…
Remarks on "Successive Convexification: A Superlinearly Convergent Algorithm for Non-convex Optimal Control Problems"
Dayou Luo, Purnanand Elango, Behcet Acikmese
The purpose of this note is to highlight and address inaccuracies in the convergence guarantees of SCvx, a nonconvex trajectory optimization algorithm proposed by Mao et al. (arXiv…
Advances in Trajectory Optimization for Space Vehicle Control
Danylo Malyuta, Yue Yu, Purnanand Elango +1
Space mission design places a premium on cost and operational efficiency. The search for new science and life beyond Earth calls for spacecraft that can deliver scientific payloads…
Proportional-Integral Projected Gradient Method for Model Predictive Control
Yue Yu, Purnanand Elango, Behçet Açikmeşe
Recently there has been an increasing interest in primal-dual methods for model predictive control (MPC), which require minimizing the (augmented) Lagrangian at each iteration. We…