Simulation permits you to try ideas in dynamic, synthetic environments while collecting stimulus response data to determine the quality of the control system.

仿真让我们可以在动态的合成环境中尝试一些做法，同时可以搜集这些响应数据，从而确定控制系统的品质。

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Simulation also allows the evolution of robotics control systems, which depend on random permutations of the control system over many generations (as demonstrated by genetic algorithms).

仿真还可以允许对机器人控制系统进行革新，这依赖于很多代控制系统的随机排列（遗传算法可以证实这一点）。

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The results show that this model well conforms to the actual operation and can be used for simulation system construction, system control strategy study and dynamic performance analysis of the system.

结果证明此模型能够与实际运行情况很好地吻合，可用于仿真系统的构建、系统控制策略的研究及系统动态性能的分析等。

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