MODEL-FREE ADAPTIVE CONTROL APPROACH FOR CABLE-DRIVEN PARALLEL ROBOT

Abstract

When a mathematical model is not available and system-specific conditions are fulfilled, a model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique with a pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time cable robot system. The key control ideal is that an estimation of real-time system parameters that represent system dynamic variations is realized by using only inputs and outputs. Then the proposed controller is successfully implemented in a cable-driven parallel robot (CDPR) to control the position of the end-effector (EE). This MFAC was applied and demonstrated satisfactory performance on an actual CDPR platform.