  This paper revisits the problem of optimal control law design for linear
systems using the global optimal control framework introduced by Vadim Krotov.
Krotov's approach is based on the idea of total decomposition of the original
optimal control problem (OCP) with respect to time, by an $ad$ $hoc$ choice of
the so-called Krotov's function or solving function, thereby providing
sufficient conditions for the existence of global solution based on another
optimization problem, which is completely equivalent to the original OCP. It is
well known that the solution of this equivalent optimization problem is
obtained using an iterative method. In this paper, we propose suitable Krotov's
functions for linear quadratic OCP and subsequently, show that by imposing
convexity condition on this equivalent optimization problem, there is no need
to compute an iterative solution. We also give some key insights into the
solution procedure of the linear quadratic OCP using the proposed methodology
in contrast to the celebrated Calculus of Variations (CoV) and
Hamilton-Jacobi-Bellman (HJB) equation based approach.
