并证明了算法收敛性。

Convergence of the algorithm is proved.

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本文研究系统状态初值漂移和系统参数扰动对迭代学习控制算法收敛性的影响。

In this paper, the influence about system initial shift and system parameter disturbance on convergence of the algorithm is studied.

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该算法克服了DFS算法收敛性差和模拟退火(SA)算法收敛速度慢的缺点。

Compared with traditional DFS algorithm and simulated annealing (SA) algorithm, the proposed algorithm possesses better convergency and high convergence rate.

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