The following paper presents the design, implementation, and validation of a new adaptive control system based on the Modified Function Approximation Technique (MFAT) augmented with backstepping control for a haptic robot with unknown dynamic and actuator parameters, employed in a spinal surgical simulator. The combination of backstepping control and the MFAT policy ensures the continuous performance tracking of the haptic manipulator's trajectories using state and output feedback. Contrary to the conventional FAT, the use of basis functions in dynamic and actuator parameter approximations is completely eliminated. Besides, the proposed control scheme was improved by integrating a high order sliding mode observer to eliminate the need for velocity measurements. Consequently, offline simulation and comparative studies were carried out to validate the effectiveness of the proposed control scheme, and controlled experimental cases were conducted using the haptic manipulator (Entact W3C) for validating the system in real time.

以下论文介绍了一种新的自适应控制系统的设计、实现和验证，该系统基于改进的函数逼近技术 (MFAT)，并在脊柱手术模拟器中使用了具有未知动态和执行器参数的触觉机器人的反步控制。反步控制和 MFAT 策略的结合确保了使用状态和输出反馈对触觉操纵器轨迹的连续性能跟踪。与传统的 FAT 不同，在动态和执行器参数近似中使用基函数被完全消除。此外，通过集成一个高阶滑模观测器来改进所提出的控制方案，以消除对速度测量的需要。最后，