Obtaining a Model and Control for a Rigid Body Motion System. 1st Report. Obtaining Inertia Parameters of a Rigid Body and Electromagnetic characteristics for a Magnetic Levitation System.

Abstract

This paper proposes a control method for a nonlinear rigid body motion system using motion system using motion learning. Motion learning is defined as achievement of an objective motion control by obtaining a model of the motion system. The proposed control structure consists of feedback controllers to stabilizes the unstable motion system, a gain tuner to obtain the nonlinear model and linearize the motion system; and an inverse motion system to generate inputs to be applied to the linearized motion system. The obtained model is described as series of weighted basis functions, and the explicit learning rules of weights are derived using Popov's hyperstable theory. The tuning rules of feedback gains are determined using the obtained nonlinear models. Further, this paper shows the high performance of the proposed method demonstrating an experiment of the tracking desired trajectory in the electromagnetic levitation and positioning system.