  In this paper, co-states are used to develop a framework that desensitizes
the optimal cost. A general formulation for an optimal control problem with
fixed final time is considered. The proposed scheme involves elevating the
parameters of interest into states, and further augmenting the co-state
equations of the optimal control problem to the dynamical model. A running cost
that penalizes the co-states of the targeted parameters is then added to the
original cost function. The solution obtained by minimizing the augmented cost
yields a control which reduces the dispersion of the original cost with respect
to parametric variations. The relationship between co-states and the cost-to-go
function, for any given control law, is established substantiating the
approach. Numerical examples and Monte-Carlo simulations that demonstrate the
proposed scheme are discussed.
