We present two related anytime algorithms for control of nonlinear systems
when the processing resources available are time-varying. The basic idea is to
calculate tentative control input sequences for as many time steps into the
future as allowed by the available processing resources at every time step.
This serves to compensate for the time steps when the processor is not
available to perform any control calculations. Using a stochastic Lyapunov
function based approach, we analyze the stability of the resulting closed loop
system for the cases when the processor availability can be modeled as an
independent and identically distributed sequence and via an underlying Markov
chain. Numerical simulations indicate that the increase in performance due to
the proposed algorithms can be significant.Comment: 14 page