Iterative Learning Tracking Control of a Hybrid-Driven Based Three-Cable Parallel Manipulator

Abstract

The aim of this work was to present iterative learning tracking control of a hybrid-driven based three-cable parallel manipulator (HDCPM). The HDCPM has the advantages of both cable parallel manipulator and hybrid-driven planar five-bar mechanism. Design of the HDCPM is described and dynamic model is developed on the basis of Lagrange method. Consider the HDCPM system with nonlinear, time-varying characteristics and repetitive unknown disturbances; an adaptive iterative learning control strategy, which can control gains change with the iterations, is designed. By means of Lyapunov function, the stability of the controller is proved. Finally, simulation results indicate that a perfect trajectory tracking of the HDCPM is achieved by the adaptive iterative learning controller, which also illustrate the correctness of the dynamic modeling and effectiveness of the proposed control strategy.