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March 10, 2026Asian Journal of Control0 citations

A novel approach for performance improvement in Model Predictive Safety Certification with output tracking

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NBNasibe BastaniNBNooshin BigdeliHZHasan Zarabadipour

Key Points

  • The research aims to develop a method that enhances safety while improving performance in safety certification frameworks.
  • Introduced a Multi-Step Model Predictive Safety Certification (MPSC) scheme
  • Utilized Predictive Functional Control for output tracking
  • Employed a robust optimizer to ensure stability
  • Conducted numerical simulations to validate the method
  • Demonstrated improved performance compared to existing certification methods
  • Achieved both safety and efficiency in simulations
  • Validated robustness through comparative analysis with previous studies

Abstract

Abstract While learning‐based controllers demonstrate impressive performance, a significant challenge remains the lack of safety guarantees. Existing safety approaches often involve separating the optimization of the objective and constraint certification, which introduces a Model Predictive Safety Certification (MPSC) scheme. Unfortunately, this isolation frequently compromises performance, even though it ensures constraint satisfaction. This paper introduces a novel Multi‐Step MPSC scheme that combines Predictive Functional Control to track the reference output generated by the learning‐based controller, along with the utilization of a robust optimizer. The goal of this innovation is to introduce a method that confirms the system's safety while enhancing the performance of the MPSC. A numerical case study is provided and compared with the studies conducted by other researchers. The simulation results validate the efficiency and robustness of the proposed approach.

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Cite This Study

Bastani et al. (2026) studied this question.

synapsesocial.com/papers/69af95a470916d39fea4d78dhttps://doi.org/10.1002/asjc.70076
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