Fuzzy learning tracking of a parallel cable manipulator for the square kilometre array

The square kilometre array (SKA) is an ambitious world cooperation project to develop the next generation large radio telescope with the collecting area of 1 square kilometre. A parallel cable manipulator is used to provide large workspace and accomplish the coarse tracking of the feed. Considering the characteristics of large time-varying delay of the large span cable actuator of the parallel cable manipulator, a fuzzy model reference learning controller (FMRLC) is proposed to accomplish the coarse tracking. The FMRLC consists of a direct fuzzy controller, a reference fuzzy inverse model and a fuzzy learning mechanism. This FMRLC adjusts the direct fuzzy controller so that the closed-loop system acts like a pre-specified reference model using the fuzzy learning mechanism. The comparative simulation results with a linear PD control demonstrate the better performance of the developed fuzzy controller, which have built a solid base for the engineering implementation of the high precision tracking of the feed for the SKA.