Scholarlink

As one of the conventional Model Predictive Control (MPC) methodologies, Generalized Predictive Control (GPC) displays a significant dependency on the motor model, necessitating the real-time acquisition of precise motor parameters. To address this challenge, this study introduces an innovative ultra-local incremental model for the Permanent Magnet Synchronous Motor (PMSM). Moreover, a sliding mode observer (SMO) is deployed to enable real-time updating of the unknown variable, thereby reducing predicted current errors. Notably, the proposed model features only one unknown variable, eliminating the need for additional parameter information and showcasing remarkable parameter robustness. Furthermore, by treating parameters incorporating inductance details as controlled variables rather than fixed values with linear magnetization characteristics, this approach effectively mitigates nonlinear disturbances within the system. Subsequently, experimental results substantiate the efficacy and disturbance rejection capabilities of this novel strategy.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Model-Free Generalized Predictive Current Control for Permanent Magnet Synchronous Motor Based on Sliding Mode Observer

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Zhijie Zhou,
  • Wang Kai,
  • Feng Li,
  • Lingling Guo

摘要

As one of the conventional Model Predictive Control (MPC) methodologies, Generalized Predictive Control (GPC) displays a significant dependency on the motor model, necessitating the real-time acquisition of precise motor parameters. To address this challenge, this study introduces an innovative ultra-local incremental model for the Permanent Magnet Synchronous Motor (PMSM). Moreover, a sliding mode observer (SMO) is deployed to enable real-time updating of the unknown variable, thereby reducing predicted current errors. Notably, the proposed model features only one unknown variable, eliminating the need for additional parameter information and showcasing remarkable parameter robustness. Furthermore, by treating parameters incorporating inductance details as controlled variables rather than fixed values with linear magnetization characteristics, this approach effectively mitigates nonlinear disturbances within the system. Subsequently, experimental results substantiate the efficacy and disturbance rejection capabilities of this novel strategy.