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A TBR-based trajectory piecewise-linear algorithm for generating accurate low-order models for nonlinear analog circuits and MEMS

机译:基于TBR的轨迹分段线性算法,用于为非线性模拟电路和MEMS生成精确的低阶模型

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In this paper we propose a method for generating reduced models for a class of nonlinear dynamical systems, based on truncated balanced realization (TBR) algorithm and a recently developed trajectory piecewise-linear (TPWL) model order reduction approach. We also present a scheme which uses both Krylov-based and TBR-based projections. Computational results, obtained for examples of nonlinear circuits and a micro-electro-mechanical system (MEMS), indicate that the proposed reduction scheme generates nonlinear macromodels with superior accuracy as compared to reduction algorithms based solely on Krylov subspace projections, while maintaining a relatively low model extraction cost.
机译:在本文中,我们提出了一种基于截断平衡实现(TBR)算法和最近开发的轨迹分段线性(TPWL)模型降阶方法的非线性动力学系统简化模型生成方法。我们还提出了同时使用基于Krylov和TBR的投影的方案。从非线性电路和微机电系统(MEMS)的示例获得的计算结果表明,与仅基于Krylov子空间投影的归约算法相比,所提出的归约方案生成的非线性宏模型具有更高的精度。模型提取成本。

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