Abstract
This study proposes an adaptive control method for obtaining a model and control for a nonlinear motion system. Since the motion systems driven by electromagnetic force have strong nonlinearity, it is neccessary to obtain the model of the nonlinearity to achieve an objective motion control. The control architecture consists of a feedback system to stabilize the motion system, learning controller to obtain the model of nonlinearity and to tune the feedback gain to linearize the motion system and inverse dynamics to offset the the motion system to make motion trajectory coincide with the objective trajectory. The obtained model is described as series of weighted basis functions, and the explicit learning rules of weights are derived by using Popov's hyperstable theory. The tuning rules of feedback gains are determined by using the obtained nonlinear models. Further, this paper shows the high performance of the proposed method by demonstrating an experiment of the tracking desired trajectory in the electromagnetic levitation and positioning system.
