Moment based model predictive control for linear systems: Additive perturbations case

نویسندگان

چکیده

In this article, we present a novel linear model predictive control (MPC) strategy for controlling uncertain dynamical systems. The moment based MPC is on the (centralized) moments of stochastic cost and constraint functions. We show that formulations yield computationally tractable problems, due to explicit analytic expressions linearity in dynamics. This article considers (i) output regulation configuration, where steered towards reference state vector not correctly accessible controller at decision instants; (ii) formulation with uncertainties are non-Gaussian random variables, (iii) bound polytopic constraints problem subject either Gaussian disturbances or symmetric distributions. demonstrate effectiveness proposed technique simulation examples such as double integrator system quadruple tank system.

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ژورنال

عنوان ژورنال: International Journal of Robust and Nonlinear Control

سال: 2022

ISSN: ['1049-8923', '1099-1239']

DOI: https://doi.org/10.1002/rnc.6279