针对最优H2模型降阶问题,提出了适合大规模多输入多输出系统的共轭梯度法.该方法仅需利用一阶导数信息,存储量少,计算复杂度低,且具有超线性收敛性.实验结果显示了算法的有效性.%A conjugated gradient algorithm with super-linear convergence which is suitable for the optimal H2 model reduction of the multi-input multi-output large scale dynamical systems is proposed. The proposed algorithm computes only first-order derivative of the cost function. It has low storage requirement and computational cost. Numerical example demonstrates the approximation accuracy and computational efficiency.
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