In this paper, an application of Model Predictive Control (MPC) to physical human-machine interaction is presented. In particular, the study focuses on the development of a mechatronic device able to apply a well-controlled mechanical impulsive force on the human body, for clinical investigation of postural control. The need for high accuracy and repeatability led to the MPC design, which is able to manage the non-linearities related to the human-machine interaction. The hardware architecture design of the prototype, the development of the control system (based on motor current saturation) and its optimization are presented. The results of experimental trials carried out in the laboratory and on healthy subjects show that the MPC algorithm is able to provide the accuracy and robustness requested by the application.
Application of Model Predictive Control in Physical Human-Machine Interaction / Paterna, Maria; Pacheco Quiñones, Daniel; De Benedictis, Carlo; Maffiodo, Daniela; Franco, Walter; Ferraresi, Carlo (MECHANISMS AND MACHINE SCIENCE). - In: Advances in Service and Industrial Robotics. RAAD 2022. / Müller A., Brandstötter M.. - ELETTRONICO. - Cham : Springer, 2022. - ISBN 978-3-031-04869-2. - pp. 571-579 [10.1007/978-3-031-04870-8_67]
Application of Model Predictive Control in Physical Human-Machine Interaction
Paterna, Maria;Pacheco Quiñones, Daniel;De Benedictis, Carlo;Maffiodo, Daniela;Franco, Walter;Ferraresi, Carlo
2022
Abstract
In this paper, an application of Model Predictive Control (MPC) to physical human-machine interaction is presented. In particular, the study focuses on the development of a mechatronic device able to apply a well-controlled mechanical impulsive force on the human body, for clinical investigation of postural control. The need for high accuracy and repeatability led to the MPC design, which is able to manage the non-linearities related to the human-machine interaction. The hardware architecture design of the prototype, the development of the control system (based on motor current saturation) and its optimization are presented. The results of experimental trials carried out in the laboratory and on healthy subjects show that the MPC algorithm is able to provide the accuracy and robustness requested by the application.File | Dimensione | Formato | |
---|---|---|---|
RAAD2022 - ePGAS - Review-4.pdf
embargo fino al 23/04/2023
Descrizione: Author post-print
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
PUBBLICO - Tutti i diritti riservati
Dimensione
376.2 kB
Formato
Adobe PDF
|
376.2 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
applMPC_final_springer.pdf
non disponibili
Descrizione: Publisher post-print
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
996.1 kB
Formato
Adobe PDF
|
996.1 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2967214