A Nonlinear Decoupling Control Approach Using RBFNNI-Based Robust Pole Placement for a Permanent Magnet In-Wheel Motor

• Main Authors: Yong Li, Bin Li, Xing Xu, Xiaodong Sun
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Permanent magnet in-wheel motor; inverse system; radial basis function neural network; robust pole placement; electric vehicle
• Online Access: https://ieeexplore.ieee.org/document/8168327/

This paper presents a novel nonlinear decoupling control scheme for a permanent magnet in-wheel motor (PMIWM), in which both the radial basis function neural network inverse (RBFNNI) and the state feedback robust pole placement (RPP) are employed. First, a theoretical analysis shows the existence of the inverse system of the PMIWM to be modeled mathematically. An inverse system is introduced into the original system of the PMIWM. Then, by cascading the RBFNNI system on the left side of the original PMIWM system, a new decoupling pseudo-linear system is established. Moreover, the RPP theory is employed to design an extra controller which further improves the disturbance rejection and robustness of the whole system. The effectiveness of the proposed control approach is verified by the real-time hardware-in-the-loop experiments under various operations.