Aiming at chaotic system, this paper proposes a multi-model adaptive control strategy based on a neural-gas network with fuzzy logic.
针对混沌系统的控制问题，提出了一种基于神经气网络的模糊多模型自适应控制方法。
Based on wavelet networks and multiple model adaptive control theories, the identification and control methods for the complicated nonlinear dynamic systems are proposed.
本文以小波网络和多模型理论为基础，对复杂非线性动态系统的辨识和控制方法进行了研究。
A model switching algorithm based on multi-model adaptive control is presented to solve the problem of poor transient response in the adaptive control of nonlinear time-varying system.
针对非线性时变系统在自适应控制过程中瞬态响应差的问题，提出了一种基于多模型自适应控制的模型切换算法。
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