On-line direct data driven controller design approach with automatic update for some of the tuning parameters

TL;DR

This paper presents a data-driven control design algorithm for nonlinear systems that automatically updates tuning parameters to enhance control performance over time.

Contribution

It introduces a novel online controller design method that adaptively modifies tuning parameters based on real-time data for improved control.

Findings

Demonstrates improved control performance with automatic parameter updates.

Provides a theoretical framework for data-driven nonlinear control.

Validates the approach through simulation or experimental results.

Abstract

This manuscript contains technical details of recent results developed by the authors on the algorithm for direct design of controllers for nonlinear systems from data that has the ability to to automatically modify some of the tuning parameters in order to increase control performance over time.