Scalability Concept for Predictable Closed-Loop Response of Adaptive Controllers

TL;DR

This paper introduces a scalability concept for adaptive control that helps in tuning learning rates to ensure predictable closed-loop responses, supported by numerical examples for validation.

Contribution

It presents a novel scalability framework for adaptive controllers, enabling better predictability and validation of their responses under different command profiles.

Findings

Scalability improves the predictability of adaptive control responses.

Numerical examples demonstrate the effectiveness of the proposed concept.

Abstract

We introduce a new concept called scalability to adaptive control in this paper. In particular, we analyze how to scale learning rates of adaptive weight update laws of various adaptive control schemes with respect to given command profiles to achieve a predictable closed-loop response. An illustrative numerical example is provided to demonstrate the proposed concept, which emphasize that it can be an effective tool for validation and verification of adaptive controllers.