EconPapers    
Economics at your fingertips  
 

Using an Improved Output Feedback MPC Approach for Developing a Haptic Virtual Training System

Soroush Sadeghnejad (), Farshad Khadivar, Mojtaba Esfandiari, Golchehr Amirkhani, Hamed Moradi, Farzam Farahmand and Gholamreza Vossoughi
Additional contact information
Soroush Sadeghnejad: Amirkabir University of Technology (Tehran Polytechnic)
Farshad Khadivar: Sharif University of Technology
Mojtaba Esfandiari: Sharif University of Technology
Golchehr Amirkhani: Sharif University of Technology
Hamed Moradi: Sharif University of Technology
Farzam Farahmand: Sharif University of Technology
Gholamreza Vossoughi: Sharif University of Technology

Journal of Optimization Theory and Applications, 2023, vol. 198, issue 2, No 11, 745-766

Abstract: Abstract Haptic training simulators generally consist of three major components, namely a human operator, a haptic interface, and a virtual environment. Appropriate dynamic modeling of each of these components can have far-reaching implications for the whole system's performance improvement in terms of transparency, the analogy to the real environment, and stability. In this paper, we developed a virtual-based haptic training simulator for Endoscopic Sinus Surgery by doing a dynamic characterization of the phenomenological sinus tissue fracture in the virtual environment, using an input-constrained linear parametric variable model. A parallel robot manipulator equipped with a calibrated force sensor is employed as a haptic interface. A lumped five-parameter single-degree-of-freedom mass-stiffness-damping impedance model is assigned to the operator’s arm dynamic. A robust online output feedback quasi-min–max model predictive control framework is proposed to stabilize the system during the switching between the piecewise linear dynamics of the virtual environment. The simulations and the experimental results demonstrate the effectiveness of the proposed control algorithm in terms of robustness and convergence to the desired impedance quantities.

Keywords: Virtual reality-based haptic system; Endoscopic sinus surgery (ESS) training simulator; Linear parametric variable; Model predictive control (MPC); Robust stability; Quasi-min–max algorithm (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-023-02241-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:198:y:2023:i:2:d:10.1007_s10957-023-02241-0

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-023-02241-0

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joptap:v:198:y:2023:i:2:d:10.1007_s10957-023-02241-0