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 (ESS) 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 (MPC) 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.

翻译：合成培训模拟器通常由三个主要组成部分组成,即人类操作器、偶然界面和虚拟环境。对其中每个组成部分进行适当的动态模拟,可以对整个系统在透明度、真实环境的类比和稳定性方面的性能改进产生深远的影响。在本文件中,我们开发了一种虚拟的基于机能培训模拟器,用于Endoscopic Sinus外科手术(ESS),对虚拟环境中的苯球性脊椎骨折进行动态定性,使用一种输入限制的线性线性参数变量模型。一个配备校准力传感器的平行机器人操纵器可以用作一个机械界面。一个包装有5度单度单度自由度大规模阻力测试模型被分配给操作器的手臂动态。一个强大的在线输出反馈准中轴模型预测控制(MPC)框架建议,在虚拟环境的细线性线性动态转换期间稳定系统。模拟和实验结果显示拟议控制算法在稳健性和稳健性方面的有效性。</s>