一种实现导纳矩阵宏模型无源性的快速方法  

Fast method to enforce the passivity of macromodels for the admittance matrix

作　　者：闫旭[1] 李玉山[1] 高崧[1] 丁同浩[1] 曲咏哲[1] 

机构地区：[1]西安电子科技大学电路CAD研究所,陕西西安710071

出　　处：《西安电子科技大学学报》2011年第1期153-158,共6页Journal of Xidian University

基　　金：国家自然科学基金资助项目(60871072;60672027);国家教育部博士点基金资助项目(20050701002)

摘　　要：传统的二次规划方法使用不等式约束,并利用数值优化来补偿无源性违背,仿真时间很长.针对上述问题,提出了一种新的二次规划方法来实现宏模型的无源性.该方法在二次规划方法的基础上,用等式约束代替不等式约束,采用拉格朗日乘数法进行优化.由此优化算法所产生的线性系统通过Krylov子空间方法进行求解,可以充分利用矩阵的稀疏性,从而使求解时间大大减小.同时还给出了无源性违背的频率选择策略.实验表明,该方法的仿真时间小于传统二次规划方法的1/10.Based on inequality constraint, numerical optimization is used in the traditional quadratic programming method to compensate the passivity violations, with the required simulation time being quite large. A novel quadratic programming method to enforce the passivity of macromodels is presented, which can greatly reduce the simulation time. This method is based on the quadratic programming method with an equality constraint. The associated optimization problem can be solved by the method of Lagrange multipliers. The Krylov subspace method is adopted to solve the resulting linear system, which can fully utilize the sparsity of the problem. The computational time required for this method is significantly reduced. A frequency selection strategy for passivity violations is also introduced. Several examples show that the solving time required for the presented method is less than 1/10 that of the traditional quadratic programming method.

关 键 词：宏模型 无源性 二次规划 拉格朗日乘数 稀疏性 

分 类 号：TN801[电子电信—信息与通信工程]