This paper develops a sliding-mode based simplified structure of neuro-fuzzy speed and torque compensator incorporated with an induction motor (IM) drive deploying feedback linearization (FBL). The intuitive linearization technique with the proposed simplified structure neuro-fuzzy sliding-mode control (NFSMC) considerably improves the torque and speed responses under system uncertainty and outer load disturbance, giving optimal system performance. This proposed technique also has high computational efficiency due to single error input over conventional one and thus can easily be applied for industrial uses. The parameter tuning of the simplified neuro-fuzzy control (NFC) is done by sliding-mode control (SMC) based adaptive mechanism. The proposed simplified method based linearized drive is simulated as well as experimentally investigated using low-cost DSP2812. The responses prove that the drive system performance characteristics using proposed simplified NFSMC is well-preserved compared to that of conventional one. Additionally, it provides optimal dynamic performance and is robust in terms of parameter variations and peripheral load disturbance.

本文开发了一种基于滑模的神经模糊速度和转矩补偿器的简化结构，该结构结合了感应电动机（IM）驱动器和反馈线性化（FBL）。所提出的简化结构神经模糊滑模控制（NFSMC）的直观线性化技术极大地改善了系统不确定性和外部负载干扰下的转矩和速度响应，从而提供了最佳的系统性能。由于相对于传统技术输入了单个错误，该提出的技术还具有高计算效率，因此可以容易地应用于工业用途。简化的神经模糊控制（NFC）的参数调整是通过基于滑模控制（SMC）的自适应机制完成的。使用低成本DSP2812对提出的基于简化方法的线性化驱动进行了仿真和实验研究。响应证明，与传统的NFSMC相比，使用建议的简化NFSMC可以保持驱动系统的性能特征。此外，它还提供了最佳的动态性能，并且在参数变化和外围负载扰动方面都非常强大。