  This paper describes new results linking constrained optimization theory and
nonlinear contraction analysis. Generalizations of Lagrange parameters are
derived based on projecting system dynamics on the tangent space of possibly
time-varying constraints. The paper formalizes the intuition that, just as
convexity rather than linearity is the key property in optimization,
contraction rather than linearity is the key dynamical property in this
context.
