A low-complexity funnel control approach for non-linear systems of higher-order

We address the problem of output reference tracking for unknown non-linear multi-input, multi-output systems described by functional differential equations. This class of systems includes those with a strict relative degree, and bounded-input bounded-output (BIBO) stable internal dynamics. The objective is to ensure that the tracking error evolves within a prescribed performance funnel. To achieve this, we propose a novel model-free adaptive controller with lower complexity than existing funnel control methods, avoiding the use of non-linearities in intermediate error signals. We establish the feasibility and effectiveness of the proposed design through theoretical analysis and demonstrate its performance with simulations, comparing it to previous approaches.

Publication Details

Journal
ArXiv.org
Published
2025-03-14
Primary Topic
Vocational Education and Training
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A low-complexity funnel control approach for non-linear systems of higher-order

ArXiv.org
Vocational Education and Training
article

A low-complexity funnel control approach for non-linear systems of higher-order

article en

Abstract

We address the problem of output reference tracking for unknown non-linear multi-input, multi-output systems described by functional differential equations. This class of systems includes those with a strict relative degree, and bounded-input bounded-output (BIBO) stable internal dynamics. The objective is to ensure that the tracking error evolves within a prescribed performance funnel. To achieve this, we propose a novel model-free adaptive controller with lower complexity than existing funnel control methods, avoiding the use of non-linearities in intermediate error signals. We establish the feasibility and effectiveness of the proposed design through theoretical analysis and demonstrate its performance with simulations, comparing it to previous approaches.

ArXiv.org
Openalex Percentile: Top 38%
Vocational Education and Training
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A low-complexity funnel control approach for non-linear systems of higher-order · ArXiv.org (2025) | TGRS Research Map | TGRS