A reciprocating linear actuation system utilizing electrorheological (ER) fluid clutches is developed. In this paper, we focus on achieving accurate position control of the proposed system. In order to realize real-time application, a simple feedforward neural network with a single hidden layer is examined to model the inverse problem of torque transmission. We then develop the position controller based on the computed torque control (CTC) framework, augmented with a proportional–derivative (PD) feedback loop. Experimental results confirm that the proposed control architecture delivers robust and accurate position control, even under disturbances caused by randomly changing motor torque inputs.
Huang et al. (Thu,) studied this question.