Reference
J. Xu, T. van den Boom, L. Buşoniu, and B. De Schutter, "Model
predictive control for continuous piecewise affine systems using optimistic
optimization,"
Proceedings of the 2016 American Control
Conference, Boston, Massachusetts, pp. 4482-4487, July 2016.
Abstract
This paper considers model predictive control for continuous piecewise affine
(PWA) systems. In general, this leads to a nonlinear, nonconvex optimization
problem. We introduce an approach based on optimistic optimization to solve the
resulting optimization problem. Optimistic optimization is based on recursive
partitioning of the feasible set and is characterized by an efficient
exploration strategy seeking for the optimal solution. The advantage of
optimistic optimization is that one can guarantee bounds on the suboptimality
with respect to the global optimum for a given computational budget. The 1-norm
and ∞-norm objective functions often considered in model predictive
control for continuous PWA systems are continuous PWA functions. We derive
expressions for the core parameters required by optimistic optimization for the
resulting optimization problem. By applying optimistic optimization, a sequence
of control inputs is designed satisfying linear constraints. A bound on the
suboptimality of the returned solution is also discussed. The performance of
the proposed approach is illustrated with a case study on adaptive cruise
control.
Publisher page
Downloads
BibTeX
@inproceedings{Xuvan:16-007,
author = {Xu, Jia and van den Boom, Ton and Bu{\c{s}}oniu, Lucian and De
Schutter, Bart},
title = {Model Predictive Control for Continuous Piecewise Affine
Systems Using Optimistic Optimization},
booktitle = {Proceedings of the 2016 American Control Conference},
address = {Boston, Massachusetts},
pages = {4482--4487},
month = jul,
year = {2016}
}