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

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...

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Veröffentlicht in:	Journal of optimization theory and applications Jg. 198; H. 2; S. 745 - 766
Hauptverfasser:	Sadeghnejad, Soroush, Khadivar, Farshad, Esfandiari, Mojtaba, Amirkhani, Golchehr, Moradi, Hamed, Farahmand, Farzam, Vossoughi, Gholamreza
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2023 Springer Nature B.V
Schlagworte:	Algorithms Applications of Mathematics Calculus of Variations and Optimal Control; Optimization Control algorithms Control theory Damping Degrees of freedom Dynamic models Engineering Environment models Haptic interfaces Haptics Impedance Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Output feedback Predictive control Robot arms Simulation Simulators Theory of Computation Training simulators Virtual environments Model predictive control (MPC) Virtual reality-based haptic system Robust stability Endoscopic sinus surgery (ESS) training simulator Quasi-min–max algorithm Linear parametric variable
ISSN:	0022-3239, 1573-2878
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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.
AbstractList	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.
Author	Sadeghnejad, Soroush Esfandiari, Mojtaba Khadivar, Farshad Moradi, Hamed Farahmand, Farzam Vossoughi, Gholamreza Amirkhani, Golchehr
Author_xml	– sequence: 1 givenname: Soroush orcidid: 0000-0001-8286-7756 surname: Sadeghnejad fullname: Sadeghnejad, Soroush email: s.sadeghnejad@aut.ac.ir organization: Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic) – sequence: 2 givenname: Farshad surname: Khadivar fullname: Khadivar, Farshad organization: School of Mechanical Engineering, Sharif University of Technology – sequence: 3 givenname: Mojtaba surname: Esfandiari fullname: Esfandiari, Mojtaba organization: School of Mechanical Engineering, Sharif University of Technology – sequence: 4 givenname: Golchehr surname: Amirkhani fullname: Amirkhani, Golchehr organization: School of Mechanical Engineering, Sharif University of Technology – sequence: 5 givenname: Hamed surname: Moradi fullname: Moradi, Hamed organization: School of Mechanical Engineering, Sharif University of Technology – sequence: 6 givenname: Farzam surname: Farahmand fullname: Farahmand, Farzam organization: School of Mechanical Engineering, Sharif University of Technology – sequence: 7 givenname: Gholamreza surname: Vossoughi fullname: Vossoughi, Gholamreza organization: School of Mechanical Engineering, Sharif University of Technology
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Keywords	Model predictive control (MPC) Virtual reality-based haptic system Robust stability Endoscopic sinus surgery (ESS) training simulator Quasi-min–max algorithm Linear parametric variable
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Snippet	Haptic training simulators generally consist of three major components, namely a human operator, a haptic interface, and a virtual environment. Appropriate...
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SubjectTerms	Algorithms Applications of Mathematics Calculus of Variations and Optimal Control; Optimization Control algorithms Control theory Damping Degrees of freedom Dynamic models Engineering Environment models Haptic interfaces Haptics Impedance Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Output feedback Predictive control Robot arms Simulation Simulators Theory of Computation Training simulators Virtual environments
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Title	Using an Improved Output Feedback MPC Approach for Developing a Haptic Virtual Training System
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