System adjustment for targeted performance combining symbolic regression and set inversion

TL;DR

This paper introduces a methodology combining symbolic regression and set inversion techniques to adjust systems for targeted performance using only input-output data, leveraging evolutionary programming and set inversion algorithms.

Contribution

It presents a novel approach integrating symbolic regression with set inversion methods like PSI-algorithm for system adjustment based solely on data.

Findings

Effective system adjustment demonstrated using the proposed methodology.

Combines symbolic regression with set inversion for targeted performance.

Applicable with minimal prior information, relying only on input-output data.

Abstract

One presents methodology and algorithms to prepare a causal system in order to achieve desired performances if only input-output data are known and when no other informations are available. This can be done with mean of evolutionnary programming and set inversion methods, such as PSI-algorithm or SIvIA.