Attitude estimation of a permanent magnet spherical motor based on an improved fast discriminative scale space tracking algorithm

Abstract

A permanent magnet spherical motor (PMSM) can perform a three-degree-of-freedom operation. The estimation of the attitude of the rotor is one of the key steps for realizing the closed-loop control of PMSM. An attitude estimation method based on a target-tracking algorithm is proposed in this study. Firstly, a high-speed camera is used to capture a video sequence of the spherical motor in motion. The location of the target is obtained by introducing an improved fast discriminative scale space tracking (IFDSST) algorithm to track the video sequence. In consideration of the motor’s output shaft being covered with load, the single-target tracking algorithm is improved into a multi-target tracking algorithm. Markers, which are symmetrical with respect to the output shaft, are made on the surface of the rotor, and their attitudes are obtained from the images captured by the tracking algorithm. Secondly, the attitude of the output shaft is estimated by the coordinate transformation and the positional relationship between the markers and the output shaft. The effectiveness and superiority of the proposed algorithm are verified by comparing it with a micro-electromechanical system (MEMS) method and a fast -complementary filter (FCF) method. Three types of motor motions, including yaw, spin, and tilt, are tested in the experiments, and the average angle error or trajectory error of the proposed IFDSST method reduces around 33%, 53%, and 79% as compared with those of the MEMS and FCF methods, respectively. Experiments show that the proposed algorithm can effectively and accurately measure the attitude of the motor’s rotor.