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针对传统带延时模型的无源性和无源宏模型的指数发散问题,提出了一种实现无源延时宏模型的快速方法。在集总宏模型无源性方法的基础上构建约束函数和目标函数,并将目标函数转化为等式约束的二次优化问题,用共轭梯度法实现延时宏模型的无源性。该方法在实现无源性的基础上可以得到基于最小二乘的最优解,大幅度提高了建模效率。数值仿真例子表明了该方法的有效性与准确性。
Aiming at the exponential divergence problem of passive and passive macromodels with traditional delay model, a fast method to realize passive delay macromodel is proposed. Constraint function and objective function are constructed on the basis of the lumped macromodel passive method, and the objective function is transformed into the quadratic optimization problem of equality constraint, and the conjugate gradient method is used to realize the passiveness of delay macromodel. The method can obtain the optimal solution based on least squares based on the realization of the passiveness and greatly improve the modeling efficiency. Numerical examples show the effectiveness and accuracy of the proposed method.