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March 29, 2026IFAC-PapersOnLine0 citationsOpen Access

Robust Cascaded sub-Predictors Control of Norm-bounded Stochastic Systems

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EGEli Gershon

Key Points

  • The aim is to control norm-bounded stochastic systems using a novel cascaded predictor approach.
  • Analyzed linear stochastic uncertain systems with input delays in a discrete-time setting.
  • Applied H-infinity control under the assumption of accessible system states.
  • Utilized single LMI condition for norm-bounded uncertainty and extended application to polytopic cases.
  • Implemented a construct of two sub-predictors for enhanced performance.
  • Demonstrated improved closed-loop performance with the cascaded predictors compared to single predictor configurations.
  • Established LMI condition for robust control across various uncertainties.
  • Provided a practical example illustrating the theory's applicability.

Abstract

We consider linear input-delayed stochastic uncertain state-multiplicative systems in the discrete-time setting. The system uncertainties include both norm-bounded and polytopic type ones. An H ∞ single predictor control is applied to the norm-bounded uncertain system assuming the system states are accessible, thus rendering the system to a state delayed one and resulting in a single LMI condition. The latter application is extended to the case where an assembly of two sub-predictors are applied, resulting in an improved performance of the closed-loop control system. The solution obtained for the norm-bounded uncertain case is extended to the case where the system matrices reside in given polytope. An example is given that demonstrates the applicability of the theory.

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Cite This Study

Eli Gershon (2025) studied this question.

synapsesocial.com/papers/69c8c15ade0f0f753b39bc62https://doi.org/10.1016/j.ifacol.2026.03.007
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