J
John M. Carson
Researcher at California Institute of Technology
Publications - 49
Citations - 992
John M. Carson is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Optimal control & Model predictive control. The author has an hindex of 17, co-authored 43 publications receiving 732 citations. Previous affiliations of John M. Carson include NASA Headquarters.
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Journal ArticleDOI
Lossless Convexification of Nonconvex Control Bound and Pointing Constraints of the Soft Landing Optimal Control Problem
TL;DR: A convexification of the control constraints that is proven to be lossless enables the use of interior point methods of convex optimization to obtain optimal solutions of the original nonconvex optimal control problem.
Journal ArticleDOI
Lossless convexification of control constraints for a class of nonlinear optimal control problems
TL;DR: A convex relaxation of the nonconvex control constraints is proposed, and it is proved that the optimal solution to the relaxed problem is the globally optimal Solution to the original problem with nonconvergence constraints.
Proceedings ArticleDOI
Discretization Performance and Accuracy Analysis for the Rocket Powered Descent Guidance Problem
Danylo Malyuta,Taylor P. Reynolds,Michael Szmuk,Mehran Mesbahi,Behcet Acikmese,John M. Carson +5 more
Journal ArticleDOI
Dual Quaternion Based Powered Descent Guidance with State-Triggered Constraints.
Taylor P. Reynolds,Michael Szmuk,Danylo Malyuta,Mehran Mesbahi,Behcet Acikmese,John M. Carson +5 more
TL;DR: This paper presents a numerical algorithm for computing 6-degree-of-freedom free-final-time powered descent guidance trajectories that includes a special line of sight constraint that is enforced only within a specified band of slant ranges relative to the landing site.
Proceedings ArticleDOI
A model predictive control technique with guaranteed resolvability and required thruster silent times for small-body proximity operations
John M. Carson,Behcet Acikmese +1 more
TL;DR: The robust guidance and control algorithm with resolvability is demonstrated in the simulation of a spacecraft landing onto a small asteroid possessing a significant gravity field; incorporating a gravity model into the algorithm provides notable improvements in controller performance.