Decoupling Control of Outer Rotor Coreless Bearingless Permanent Magnet Synchronous Generator Based on Fuzzy Neural Network Inverse System

The outer rotor coreless bearingless permanent magnet synchronous generator (ORC-BPMSG) is a complex system with multivariable, nonlinear, and strong coupling. So, the dynamic decoupling of generation voltage and suspension force is the key to realize stable power generation and reliable operation. In this article, a decoupling control method based on fuzzy neural network (FNN) inverse system is proposed. First, the basic structure and working principle of the ORC-BPMSG are introduced in this article, and the mathematical model of the generating voltage and suspension force is established. Then, based on the reversibility analysis of the mathematical model, the inverse system is constructed by using FNN. By connecting the inverse system in series with the original system, the original nonlinear system is decoupled into three single-input and single-output linear subsystems. Finally, the designed control system is simulated and experimentally studied. The simulation and experimental results show that this control method can realize decoupling among generation voltage and suspension forces, and the ORC-BPMSG has good dynamic performance and stability.

Automated summary

This article proposes a decoupling control method based on fuzzy neural network (FNN) inverse system for the outer rotor coreless bearingless permanent magnet synchronous generator (ORC-BPMSG). The method can achieve decoupling between generation voltage and suspension force, improving the dynamic performance and stability of the ORC-BPMSG.