Upper and lower envelope representations are developed for value functions
associated with problems of optimal control and the calculus of variations
that are fully convex, in the sense of exhibiting convexity in both the sta
te and the velocity. Such convexity is used in dualizing the upper envelope
representations to get the lower ones, which have advantages not previousl
y perceived in such generality and in some situations can be regarded as fu
rnishing, at least for value functions, extended Hopf-Lax formulas that ope
rate beyond the case of state-independent Hamiltonians.
The derivation of the lower envelope representations centers on a new funct
ion called the dualizing kernel, which propagates the Legendre-Fenchel enve
lope formula of convex analysis through the underlying dynamics. This kerne
l is shown to be characterized by a kind of double Hamilton-Jacobi equation
and, despite overall nonsmoothness, to be smooth with respect to time and
concave-convex in the primal and dual states. It furnishes a means whereby,
in principle, value functions and their subgradients can be determined thr
ough optimization without having to deal with a separate, and typically muc
h less favorable, Hamilton-Jacobi equation for each choice of the initial o
r terminal cost data.