Nonlinear adaptive impedance control of a haptic interaction use in endoscopic sinus surgery simulation system

Abstract

The bilateral teleoperation technique has garnered significant attention due to its effectiveness in performing tasks in surgical applications and simulators. The Novint Falcon robot combines affordability, haptic feedback, and versatility, making it a valuable tool for advancing haptic and teleoperation technologies. It can be used as a training simulator for otolaryngology surgery, a field that involves both hard and soft tissues, making it particularly challenging. A proper controller is essential to ensure the stability of such systems. This research proposes a robust adaptive sliding mode control approach for a one-degree-of-freedom Falcon robot. The strategy adjusts the impedance to a predefined nonlinear impedance model that approximates the properties of sino-nasal tissue. The stability of the proposed control method and the convergence of the tracking error are proven using the Lyapunov stability theorem. Simulation and experimental studies demonstrate the effectiveness of the proposed controller. Additionally, a comparison with an adaptive sliding mode controller without a robust term highlights that while both controllers achieve trajectory tracking, the proposed controller achieves significantly lower tracking errors. This error for robust adaptive control falls below 0.005 after a few seconds. However, the tracking error for adaptive control without robustness is notably larger.