**Reference:**

J. Xu,
T. van den Boom,
L. Busoniu, 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.

Online version of the paper

Corresponding technical report: pdf file (186 KB)

@inproceedings{Xuvan:16-007,

author={J. Xu and T. van den Boom and L. Bu{\c{s}}oniu and B. {D}e Schutter},

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},

doi={10.1109/ACC.2016.7526058}

}

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