In this letter we consider discrete-time linear systems affected by unbounded multiplicative noise. To control this class of systems, we apply an indirect-feedback stochastic model predictive control scheme that results in formally provable mean square convergence and closed-loop chance constraint satisfaction guarantees. The benefits of the proposed controller will be highlighted on a numerical example.
Stochastic MPC for Linear Systems With Unbounded Multiplicative Noise Guaranteeing Closed-Loop Chance Constraints Satisfaction
Daniele Ravasio;Marcello Farina;
2024-01-01
Abstract
In this letter we consider discrete-time linear systems affected by unbounded multiplicative noise. To control this class of systems, we apply an indirect-feedback stochastic model predictive control scheme that results in formally provable mean square convergence and closed-loop chance constraint satisfaction guarantees. The benefits of the proposed controller will be highlighted on a numerical example.File in questo prodotto:
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