Dynamic Magnetic Field Generation With High Accuracy Modeling Applied to Magnetic Robots

Abstract

Magnetic field driving technology is one of the research focuses in the field of micro/nanorobot motion control. In order to enhance the accuracy of magnetic field generation, a new drive circuit using the bipolar linear power amplifier, instead of the traditional switching elements, is designed for electromagnetic coil in this article. Meanwhile, an advanced control strategy is proposed to improve the dynamic and steady-state performance of magnetic field generation. The proposed approach mainly consists of the intelligent algorithm of neural network (NN) and proportional resonant differential feed-forward (PRDF) method. The NN algorithm is used to obtain the optimal parameters for the PRDF model. The feed-forward control is applied to eliminate the system disturbance caused by the coil temperature rise. Finally, comparative experiments with different control schemes are conducted for the combined coils of Maxwell and Helmholtz with multiple degrees of freedom. The experimental validations have revealed strong adaptability of the proposed scheme for different types of electromagnetic coils, as well as the satisfactory dynamic performance and steady-state precision.