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Model Reduction for Systems with Low-Dimensional Chaos

机译:低维混沌系统的模型减少

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A method for deriving a reduced model of a continuous-time dynamical system with low-dirnensional chaos is discussed. The method relies on the identification of peak-to-peak dynamics, i.e. the possibility of approximately (but accurately) predicting the next peak amplitude of an output variable from the knowledge of at most the two previous peaks. The reduced model is a simple one-dimensional map or, in the most complex case, a set of one-dimensional maps. Its use in control system design is discussed by means of some examples.
机译:讨论了具有低潜艇混沌的连续动态系统的降低模型的方法。该方法依赖于峰值到峰值动态的识别,即大致(但精确地)的可能性预测输出变量的下一个峰值幅度,从最初的两个先前峰值的知识。减少的模型是一个简单的一维图,或者在最复杂的情​​况下,一组一维图。其在控制系统设计中的使用是通过一些示例讨论的。

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