The significance of employing a controller in prosthetic hands cannot be overstated, as it plays a crucial role in enhancing the functionality and usability of these systems. This paper introduces an adaptive neuro-controller specifically developed for a tendon-driven soft continuum wrist of a prosthetic hand. Kinematic and dynamic modeling of the wrist is carried out using the Timoshenko beam theory. A Neural Network (NN) based strategy is adopted to predict the required motor currents to manipulate the wrist tendons from the errors in the deflection of the wrist section. The Timoshenko beam theory is used to compute the required tendon tension from the input motor current. A comparison of the adaptive neuro-controller with other similar controllers is conducted to analyze the performance of the proposed approach. Simulation studies and experimental validations of the fabricated wrist are included to demonstrate the effectiveness of the controller.

翻译：在假肢手中采用控制器的重要性不言而喻，因为它对于提升这些系统的功能性和可用性起着至关重要的作用。本文介绍了一种专门为假肢手的肌腱驱动软体连续体手腕开发的自适应神经控制器。采用铁木辛柯梁理论对手腕进行了运动学和动力学建模。采用基于神经网络（NN）的策略，根据手腕截面偏转误差来预测驱动手腕肌腱所需的电机电流。铁木辛柯梁理论用于根据输入的电机电流计算所需的肌腱张力。通过将自适应神经控制器与其他类似控制器进行比较，分析了所提方法的性能。研究包含了仿真实验以及对所制造手腕的实验验证，以证明该控制器的有效性。