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Fuzzy Neural Network Control and Identification for Uncertain Nonlinear Systems

机译:不确定非线性系统的模糊神经网络控制与辨识

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In this paper, the problem of identi.cation and control of uncertain nonlinear systems is investigated based on fuzzy neural network. The considered systems are unknown and with external disturbances, so fuzzy neural networks are employed to approximate the unknown system functions. By doing this, an identi.cation model of the controlled system can be obtained. Based on this model, a controller with adaptive mechanism can be designed for the system. The controller can attenuate the external disturbance to a given level, and guarantee the stability of the closed-loop system. Satisfactory identification and control of the system can be realized at the same time. Simulation example is given to demonstrate the effectiveness of the proposed controller.
机译:本文研究了基于模糊神经网络的不确定非线性系统的辨识与控制问题。所考虑的系统是未知的并且具有外部干扰,因此采用模糊神经网络来近似未知系统的功能。通过这样做,可以获得受控系统的识别模型。基于此模型,可以为系统设计具有自适应机制的控制器。控制器可以将外部干扰衰减到给定水平,并保证闭环系统的稳定性。可以同时实现令人满意的系统识别和控制。仿真实例证明了所提出控制器的有效性。

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