自然梯度算法有收敛速度和稳定误差两个重要指标，然而这两个指标存在内在的矛盾。
In the natural gradient algorithm, the convergence speed and stability error are two important indicators, but these two indicators are of inherent contradictions.
为了解决自然梯度算法的这个缺点，人们提出了变步长自然梯度算法，既可以获得较快的收敛速度，又可以减小稳定误差。
Variable step-size natural gradient algorithm which enjoys faster convergence speed and smaller stability error is proposed to solve the shortcoming of natural gradient algorithm.
在此基础上设计的模糊自适应控制器能够保证整个闭环系统稳定且跟踪误差收敛到零的一个邻域内。
The fuzzy adaptive controller designed based on this method can guarantees that the closed-loop system is globally stable and the tracking error converges to a neighborhood of zero.
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