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：触觉训练模拟器通常由三个主要部分组成，即操作员、触觉接口和虚拟环境。对各组成部分进行适当的动态建模，对于提升整个系统在透明度、环境逼真度以及稳定性方面的性能具有深远影响。本文通过利用输入约束线性参数可变模型对虚拟环境中鼻窦组织断裂现象进行动态表征，开发了一种用于内窥镜鼻窦手术(ESS)的虚拟触觉训练模拟器。采用配备校准力传感器的并联机器人机械臂作为触觉接口。操作员手臂动态特性被分配为集总五参数单自由度质量-刚度-阻尼阻抗模型。提出了一种鲁棒的在线输出反馈准最小-最大模型预测控制(MPC)框架，以在虚拟环境分段线性动力学切换过程中稳定系统。仿真与实验结果验证了所提控制算法在鲁棒性及收敛至期望阻抗量值方面的有效性。