Relaxing the Optimality Condition in Receding Horizon Control
Ali Jadbabie and John Hauser
Submitted, 2000 Conference on Decision and Control
Receding horizon control is based on iteratively solving an open-loop finite
horizon optimization problem. Despite its success in a variety of
industrial applications, theoretical issues such as stability were not
completely addressed until recently. It was shown in previous work that by utilizing
a suitable Control Lyapunov Function (CLF) as terminal cost, the stability
of the receding horizon scheme can be guaranteed and the region of
attraction of the receding horizon controller can be estimated. The key
point in this approach, which made it different from others, was removal of
additional stability constraints, hence making the optimizations much
easier to solve. A requirement implied in the previous results was being
able to solve the optimizations globally. In this paper, that assumption
is removed and it is shown that the optimality can be replaced by an
improvement property. A numerical example using the inverted pendulum is
presented to illustrate this point.
Conference Paper
(postscript)