Quantization and Security Parameter Design for Overflow-Free Confidential FRIT

TL;DR

This paper presents a systematic method for selecting quantization and security parameters in encrypted control tuning to prevent overflow and ensure accuracy, supported by analytical conditions and numerical validation.

Contribution

It introduces explicit analytical conditions for parameter design in encrypted control, linking quantization errors to tuning accuracy and overflow prevention.

Findings

Derived analytical conditions for overflow-free parameter selection

Quantitative relationship between quantization errors and tuning accuracy

Numerical example demonstrating effective parameter design

Abstract

This study proposes a systematic design procedure for determining the quantization gain and the security parameter in the Confidential Fictitious Reference Iterative Tuning (CFRIT), enabling overflow-free and accuracy-guaranteed encrypted controller tuning. Within an encrypted data-driven gain tuning, the range of quantization errors induced during the encoding (encryption) process can be estimated from operational data. Based on this insight, explicit analytical conditions on the quantization gain and the security parameter are derived to prevent overflow in computing over encrypted data. Furthermore, the analysis reveals a quantitative relationship between quantization-induced errors and the deviation between the gains obtained by CFRIT and non-confidential Fictitious Reference Iterative Tuning (FRIT), clarifying how parameter choice affects tuning accuracy. A numerical example verifies the proposed procedure by demonstrating that the designed parameters achieve accurate encrypted tuning within a prescribed tolerance while preventing overflow. In addition, the admissible region of parameter combinations is visualized to examine the characteristics of feasible and infeasible regions, providing practical insights into parameter design for encrypted data-driven control.