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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-reachingimplications for the whole system's performance improvement in terms oftransparency, the analogy to the real environment, and stability. In thispaper, we developed a virtual-based haptic training simulator for EndoscopicSinus Surgery (ESS) by doing a dynamic characterization of the phenomenologicalsinus tissue fracture in the virtual environment, using an input-constrainedlinear parametric variable model. A parallel robot manipulator equipped with acalibrated force sensor is employed as a haptic interface. A lumpedfive-parameter single-degree-of-freedom mass-stiffness-damping impedance modelis assigned to the operator's arm dynamic. A robust online output feedbackquasi-min-max model predictive control (MPC) framework is proposed to stabilizethe system during the switching between the piecewise linear dynamics of thevirtual environment. The simulations and the experimental results demonstratethe effectiveness of the proposed control algorithm in terms of robustness andconvergence to the desired impedance quantities.

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