Railway Wheelset Active Control and Stability via Higher Order Neural Units

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F23%3A00366597" target="_blank" >RIV/68407700:21220/23:00366597 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60076658:12310/23:43907331

Výsledek na webu

<a href="https://doi.org/10.1109/TMECH.2023.3258909" target="_blank" >https://doi.org/10.1109/TMECH.2023.3258909</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TMECH.2023.3258909" target="_blank" >10.1109/TMECH.2023.3258909</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Railway Wheelset Active Control and Stability via Higher Order Neural Units

Popis výsledku v původním jazyce

This article investigates an unconventional approach to solving the control of lateral displacement for railway bogie wheelsets using recurrent higher order neural units (HONUs). Although studies addressing control of independently rotating wheelsets have shown promising results, they are rarely applied by railway manufacturers. Research and developments in modern bogie design are trending toward active yaw control design as an extension to conventional wheelsets mechanics, particularly for higher speeds. We investigate a model-reference architecture for active control via setpoint tracking of lateral displacement. Then, a new HONU sliding mode architecture is derived to solve convergence for zero lateral displacements in higher running speeds which is a more profoundly complex issue in maintaining minimal hunting motion. Starting from the property of nonlinear polynomial architecture of HONUs with in-parameter linearity, we derive a time-variant state-space representation via nonlinear identical decomposition. Then, an input-to-state stability (ISS) approach is applied to prove the local asymptotic convergence of the applied algorithm in each state point and the bounded-input-bounded-state stability of the entire nonlinear adaptive control loop. Using ISS theory, we also prove the global asymptotic stability of the HONU sliding mode controller for the actively controlled wheelset system. The techniques are validated by simulations and a real roller rig system.

Název v anglickém jazyce

Railway Wheelset Active Control and Stability via Higher Order Neural Units

Popis výsledku anglicky

This article investigates an unconventional approach to solving the control of lateral displacement for railway bogie wheelsets using recurrent higher order neural units (HONUs). Although studies addressing control of independently rotating wheelsets have shown promising results, they are rarely applied by railway manufacturers. Research and developments in modern bogie design are trending toward active yaw control design as an extension to conventional wheelsets mechanics, particularly for higher speeds. We investigate a model-reference architecture for active control via setpoint tracking of lateral displacement. Then, a new HONU sliding mode architecture is derived to solve convergence for zero lateral displacements in higher running speeds which is a more profoundly complex issue in maintaining minimal hunting motion. Starting from the property of nonlinear polynomial architecture of HONUs with in-parameter linearity, we derive a time-variant state-space representation via nonlinear identical decomposition. Then, an input-to-state stability (ISS) approach is applied to prove the local asymptotic convergence of the applied algorithm in each state point and the bounded-input-bounded-state stability of the entire nonlinear adaptive control loop. Using ISS theory, we also prove the global asymptotic stability of the HONU sliding mode controller for the actively controlled wheelset system. The techniques are validated by simulations and a real roller rig system.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20301 - Mechanical engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE-ASME TRANSACTIONS ON MECHATRONICS

ISSN

1083-4435

e-ISSN

1941-014X

Svazek periodika

28

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

2964-2975

Kód UT WoS článku

000980408200001

EID výsledku v databázi Scopus

2-s2.0-85159718436