Output Feedback Stochastic Model Predictive Control for Linear Systems with Convex Optimization Approach

Elham Banapour, Peyman Bagheri*, Farzad Hashemzadeh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a stochastic model predictive controller is designed for discrete time linear time invariant systems, considering additive disturbance and stochastic constraints. As we know, in practical applications, measuring all state information of a system is not generally possible or affordable. So, in this work, an output feedback law is assumed as the control law. By utilizing the Chebyshev inequality and Schur complement, it is tried to convert a stochastic non-convex optimization problem into a deterministic convex optimization problem. Simulation results demonstrate the effectiveness of the proposed methodology.

Original languageEnglish
Pages (from-to)1199-1208
Number of pages10
JournalIranian Journal of Science and Technology - Transactions of Electrical Engineering
Volume48
Issue number3
DOIs
Publication statusPublished - Sept 2024

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Shiraz University 2024.

Keywords

  • Constraint handling
  • Convex optimization
  • Noise
  • Stochastic model predictive control

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