  This paper introduces a novel closed-form strategy that dynamically modifies
the reference of a pre-compensated nonlinear system to ensure the satisfaction
of a set of convex constraints. The main idea consists of translating
constraints in the state space into constraints on the Lyapunov function and
then modulating the reference velocity so as to limit the value of the Lyapunov
function. The theory is introduced for general nonlinear systems subject to
convex constraints. In the case of polyhedric constraints, an explicit solution
is provided for the large and highly relevant class of nonlinear systems whose
Lyapunov function is lower-bounded by a quadratic form. In view of improving
performances, further specializations are provided for the relevant cases of
linear systems and robotic manipulators.
