Reference
J. Xu, T. van den Boom, and B. De Schutter, "Model predictive control for
stochastic max-plus linear systems with chance constraints,"
IEEE Transactions on Automatic Control, vol. 64, no. 1, pp.
337-342, 2019.
Abstract
The topic of this paper is model predictive control (MPC) for max-plus linear
systems with stochastic uncertainties the distribution of which is supposed to
be known. We consider linear constraints on the inputs and the outputs. Due to
the uncertainties, these linear constraints are formulated as probabilistic or
chance constraints, i.e., the constraints are required to be satisfied with a
predefined probability level. The proposed chance constraints can be
equivalently rewritten into a max-affine (i.e., the maximum of affine terms)
form if the linear constraints are monotonically nondecreasing as a function of
the outputs. Based on the resulting max-affine form, two methods are developed
for solving the chance-constrained MPC problem for stochastic max-plus linear
systems. Method 1 uses Boole's inequality to convert the multivariate chance
constraint into univariate chance constraints for which the probability can be
computed more efficiently. Method 2 employs Chebyshev's inequality and
transforms the chance constraint into linear constraints on the inputs. The
simulation results for a production system example show that the two proposed
methods are faster than the Monte Carlo simulation method and yield lower
closed-loop costs than the nominal MPC method.
Publisher page
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Erratum
- T. J. J. van den Boom, J. Xu, and B. De Schutter, "Corrections to "Model predictive control for stochastic max-plus linear systems with chance constraints", [IEEE Trans. on Aut. Control, 64(1): 337-342, 2019]," IEEE Transactions on Automatic Control, vol. 65, no. 2, pp. 905-906, Feb. 2020. (online version
,  abstract,  bibtex,  tech. report (pdf))
BibTeX
@article{Xuvan:17-016,
author = {Xu, Jia and van den Boom, Ton and De Schutter, Bart},
title = {Model Predictive Control for Stochastic Max-Plus Linear Systems
with Chance Constraints},
journal = {IEEE Transactions on Automatic Control},
volume = {64},
number = {1},
pages = {337--342},
year = {2019}
}