Designing Controller for the 2-DoF Cable-Driven Serial Robot with Variable Configuration based on Adaptive Neuro-Fuzzy Systems

This paper addresses the problem of actuation and design of a controller for a 2-DoF Cable-Driven Serial Chain (CDSC) with variable configuration based on adaptive neuro-fuzzy systems. The mentioned structure uses several light cables to actuate rigid links of a passive planar serial robot, performing a 2-DoF motion pattern, which can apply tensile forces for moving the links and thus produce the necessary torque to track the desired reference model by the robot’s end-effector. Additionally, cable attachment point coordinates of the CDSC are considered variable configurations. So, a novel concept is expressed in the calculation of the CDSC’s Jacobian matrix. In this mechanism, upon formulating the sliding mode error dynamics, an Adaptive Neural Network (ANN) is used to cope with complex mathematical calculations of the CDSC dynamics. Then, the coordinates of cables are considered as variables that depend on the main states of the plant. These co-states are adaptively determined by applying an appropriate fuzzy system. As a result, an Adaptive Neuro-Fuzzy Controller (ANFC) algorithm is introduced for the mentioned redundant mechanism. Finally, by defining a new Cost of Redundancy (CoR), an optimal configuration of the cables is found, so the maximum Degrees of Redundancy (DoR) is obtained. The simulation results indicate that using the ANFC algorithm leads to a reduction of 2.23% in the CoR for the 2-DoF CDSC.