Verification and Validation of Advanced Control Systems for a Spinal Joint Wear Simulator.

Fuzzy-PI controller Leeds spinal wear simulator SIMO fuzzy logic control system activities of daily living (ADLs) hardware-in-the-loop (HiL) simulation

Journal

Bioengineering (Basel, Switzerland)
ISSN: 2306-5354
Titre abrégé: Bioengineering (Basel)
Pays: Switzerland
ID NLM: 101676056

Informations de publication

Date de publication:
01 Aug 2024
Historique:
received: 14 06 2024
revised: 05 07 2024
accepted: 23 07 2024
medline: 31 8 2024
pubmed: 31 8 2024
entrez: 29 8 2024
Statut: epublish

Résumé

Wear simulation aims to assess wear rates and their dependence on factors like load, kinematics, temperature, and implant orientation. Despite its significance, there is a notable gap in research concerning advancements in simulator control systems and the testing of clinically relevant waveforms. This study addresses this gap by focusing on enhancing the conventional proportional-integral-derivative (PID) controller used in joint simulators through the development of a fuzzy logic-based controller. Leveraging a single-input multiple-output (SIMO) fuzzy logic control system, this study aimed to improve displacement control, augmenting the traditional proportional-integral (PI) tuning approach. The implementation and evaluation of a novel Fuzzy-PI control algorithm were conducted on the Leeds spine wear simulator. This study also included the testing of dailyliving (DL) profiles, particularly from the hip joint, to broaden the scope of simulation scenarios. While both the conventional PI controller and the Fuzzy-PI controller met ISO tolerance criteria for the spine flexion-extension (FE) profile at 1 Hz, the Fuzzy-PI controller demonstrated superior performance at higher frequencies and with DL profiles due to its real-time adaptive tuning capability. The Fuzzy-PI controller represents a significant advancement in joint wear simulation, offering improved control functionalities and more accurate emulation of real-world physiological dynamics.

Identifiants

pubmed: 39199737
pii: bioengineering11080779
doi: 10.3390/bioengineering11080779
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : EU Horizon H2020 research and innovation program - Nu-Spine.
ID : 812765.

Auteurs

Kaushikk Ravender Iyer (KR)

Key Engineering Solutions Limited, Nexus Discovery Way, Leeds LS2 3AA, UK.
School of Mechanical Engineering, University of Leeds, Woodhouse, Leeds LS2 9JT, UK.

David Keeling (D)

Key Engineering Solutions Limited, Nexus Discovery Way, Leeds LS2 3AA, UK.

Richard M Hall (RM)

College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.

Classifications MeSH