I don't know which paper they mean, but here's a relevant paragraph from one of the papers available from Blackmore's page: "In this paper, we unify the convex

I don't know which paper they mean, but here's a relevant paragraph from one of the papers available from Blackmore's page: "In this paper, we unify the convex optimization approaches of [1], [2], [17] and extend them to handle thrust pointing constraints. While convexifying the problem with nonconvex thrust pointing constraints, we develop a geometrical insight into the problem that establishes a connection with “normal systems” [18]. A normal linear system is defined in the context of optimal control theory where the system is said to be normal with respect a set of feasible controls if it maximizes the Hamiltonian at a unique point of the set of feasible controls. In the case when the set of feasible controls is convex, a system being normal implies that the Hamiltonian is maximized at an extreme point of the set [18]. Our convexification result has a similar geometric interpretation since it establishes lossless convexification by ensuring that the Hamiltonian is maximized at the extreme points of a projection of the relaxed set of feasible controls. This set is then shown to be contained in the original nonconvex set of feasible controls, thereby estab- lishing that we can obtain optimal solutions of the original nonconvex problem via solving its convex relaxation."