**Reference:**

K. Máthé,
L. Busoniu,
R. Munos, and
B. De Schutter,
"Optimistic planning with a limited number of action switches for
near-optimal nonlinear control," *Proceedings of the 53rd IEEE
Conference on Decision and Control*, Los Angeles, California, pp.
3518-3523, Dec. 2014.

**Abstract:**

We consider infinite-horizon optimal control of nonlinear systems
where the actions (inputs) are discrete. With the goal of limiting
computations, we introduce a search algorithm for action sequences
constrained to switch at most a given number of times between
different actions. The new algorithm belongs to the *optimistic
planning* class originating in artificial intelligence, and is
called *optimistic switch-limited planning* (OSP). It inherits
the generality of the OP class, so it works for nonlinear, nonsmooth
systems with nonquadratic costs. We develop analysis showing that the
switch constraint leads to polynomial complexity in the search
horizon, in contrast to the exponential complexity of state-of-the-art
OP; and to a correspondingly faster convergence. The degree of the
polynomial varies with the problem and is a meaningful measure for the
difficulty of solving it. We study this degree in two representative,
opposite cases. In simulations we first apply OSP to a problem where
limited-switch sequences are near-optimal, and then in a networked
control setting where the switch constraint must be satisfied in
closed loop.

Online version of the paper

Corresponding technical report: pdf file (179 KB)

@inproceedings{MatBus:14-024,

author={K. M{\'{a}}th{\'{e}} and L. Bu{\c{s}}oniu and R. Munos and B. {D}e Schutter},

title={Optimistic planning with a limited number of action switches for near-optimal nonlinear control},

booktitle={Proceedings of the 53rd IEEE Conference on Decision and Control},

address={Los Angeles, California},

pages={3518--3523},

month=dec,

year={2014},

doi={10.1109/CDC.2014.7039935}

}

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