Modeling and Adaptive Control for Tendon Sheath Artificial Muscle Actuated Bending-Tip Systems With Unknown Parameters and Input Hysteresis: An Experimental Research

Abstract

Due to the flexible structure and extension capacity, the tendon-sheath artificial muscle (TSAM) actuated bending-tip (TAB) system has attracted increasing efforts in the field of rehabilitation and surgical robots. However, the TAB system usually suffers from unknown input hysteresis, unidentifiable parameters, and unexpected external disturbance, which bring great challenges for precise dynamic modeling and robust controller design. So far, there is still no available strategy to deal with these complicated nonlinearities for the TAB system. In this paper, the Euler-Lagrange dynamics is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first</i> established for the TAB system based on rigorous energy analysis. Then, a novel adaptive controller is developed based on the original dynamics <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">without</i> any approximation, which can suppress the unavoidable effects of unknown parameters and input hysteresis, and achieve high-precision tracking performance, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">simultaneously</i> . Specially, the proposed adaptive method can also weaken the widely-used constant curvature assumption. By utilizing the Lyapunov-based technique, the stability of the closed-loop system is proven. Finally, to further validate the effectiveness and the robustness of the proposed controller, a series of hardware experiments are carried out on a self-built flexible ureteroscopy robot.