Design an Adaptive PID Control Based on RLS with a Variable Forgetting Factor for a Reconfigurable Cable-Driven Parallel Mechanism

Abstract

This paper proposes a two-layer adaptive proportional–integral–derivative (PID) controller for precise pose control of a six-degree-of-freedom cable-driven parallel robot with eight cables, specifically designed to handle dynamic changes caused by the movement of attachment points. The positions of the attachment points on the base are adjusted to avoid collisions between humans and cables, where humans and robots are working in a shared workspace. The inherent nonlinearity of the robot system was addressed using model identification based on the recursive least squares (RLS) algorithm equipped with an adaptive forgetting factor. This method enables real-time updates to the dynamic model of the robot, thereby ensuring accurate parameter estimation as the attachment points move. The combination of the PID controller and RLS algorithm enhances the system’s ability to respond effectively to changing dynamics. Simulation results highlight the superior accuracy, robustness, and adaptability of the proposed approach, making it well suited for applications requiring a reliable performance in dynamic and unpredictable environments. The proposed method can guarantee human safety, while the end effector tracks the desired trajectory.