On optimization of stochastic max–min-plus-scaling systems

An approximation approach

Journal article (2017)

Authors

A.J.J. van den Boom Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
B.H.K. De Schutter Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
Optimization Moments Discrete event systems Max–min-plus-scaling systems Stochastic disturbance
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Published Date

2017

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

Abstract

A large class of discrete-event and hybrid systems can be described by a max–min-plus-scaling (MMPS) model, i.e., a model in which the main operations are maximization, minimization, addition, and scalar multiplication. Accordingly, optimization of MMPS systems appears in different problems defined for discrete-event and hybrid systems. For a stochastic MMPS system, this optimization problem is computationally highly demanding as often numerical integration has to be used to compute the objective function. The aim of this paper is to decrease such computational complexity by applying an approximation method that is based on the moments of a random variable and that can be computed analytically.