In a real‐time hybrid simulation, a transfer system is used to enforce the interface interaction between computational and physical substructures. A model‐based, multilayer nonlinear control system is developed to accommodate extensive performance variations and uncertainties in a physical substructure. The aim of this work is to extend the application of real‐time hybrid simulation to investigating failure, nonlinearity, and nonstationary behavior. This Self‐tuning Robust Control System (SRCSys) consists of two layers: robustness and adaptation. The robustness layer synthesizes a nonlinear control law such that the closed‐loop dynamics perform as intended under a broad range of parametric and nonparametric uncertainties. Sliding mode control is employed as the control scheme in this layer. Then, the adaptation layer reduces uncertainties at run time through slow and controlled learning of the control plant. The tracking performance of the SRCSys is evaluated in two experiments that have highly uncertain physical specimens.

中文翻译：

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用于非线性实时混合仿真的自调整鲁棒控制系统

在实时混合仿真中，传输系统用于强制计算和物理子结构之间的接口交互。开发了基于模型的多层非线性控制系统，以适应物理子结构中广泛的性能变化和不确定性。这项工作的目的是将实时混合仿真的应用扩展到调查故障，非线性和非平稳行为。这种自我调整的鲁棒控制系统（SRCSys）由两层组成：稳健性和适应性。鲁棒性层综合了非线性控制定律，使得闭环动力学在各种参数和非参数不确定性范围内都能按预期执行。滑动模式控制被用作该层中的控制方案。然后，自适应层通过缓慢而受控地学习控制工厂来减少运行时的不确定性。SRCSys的跟踪性能是在两个具有高度不确定的物理样本的实验中评估的。