The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system. In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller (FCMAC) is proposed to control this cable compensation system. In FCMAC, without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow. In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate. Furthermore, this approach is evaluated and its performance is discussed. The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.