The papers in this special section intends to collect ideas and recent advances from the global community in the field of improving robustness to uncertainty in the modelling, analysis and design of electric machines and drives, making possible the development of appropriate models for such components. When modelling electromechanical devices, electrical drives, and control apparatus, inevitable approximations and simplifications are required to allow for any kind of mathematical representations or performance predictions through numerical simulations. For example, such features as parasitic effects, external disturbances, sensor measurement errors, geometric details, construction defects, manufacturing tolerances, nonlinear behaviors or possible deviations in material properties and parameters often need to be neglected. All this leads to relatively idealized models, which cannot reflect the reality in a fully faithful fashion. When using such models for the purpose of analysis and design, unexpected or unwanted effects, such as prediction errors or failure to attain optimality, may arise. The challenge is to find suitable analysis and design approaches capable of assuring satisfactory results even in presence of uncertainties, thus featuring a good “robustness” with respect to modelling errors, inaccuracies, and inevitable tolerances.

中文翻译：

---

客座社论：电机和驱动器的可靠设计和分析

本节的论文旨在收集全球社区在提高电机和驱动器的建模，分析和设计的不确定性的鲁棒性方面的想法和最新进展，从而有可能为此类组件开发合适的模型。在对机电设备，电力驱动器和控制设备进行建模时，需要不可避免的近似和简化，以允许通过数值模拟进行任何形式的数学表示或性能预测。例如，通常需要忽略诸如寄生效应，外部干扰，传感器测量误差，几何细节，构造缺陷，制造公差，非线性行为或材料特性和参数可能的偏差等特征。所有这些导致了相对理想的模型，这些模型无法完全忠实地反映现实。当出于分析和设计目的使用此类模型时，可能会出现意料之外或不想要的影响，例如预测错误或无法获得最优性。面临的挑战是找到合适的分析和设计方法，即使在存在不确定性的情况下也能确保获得令人满意的结果，从而在建模误差，准确性和不可避免的公差方面具有良好的“稳健性”。