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The study and simulation of PID control based on RBF neural network

机译:基于RBF神经网络的PID控制的研究与仿真。

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The industrial control system is a complex nonlinear time-varying system, the traditional PID control is limited to linear system, and therefore the control effect is not ideal. In order to improve the control precision, this paper proposes a control method based on RBF neural network and. Firstly discrete models is identification by RBFNN controller and get PID parameters tuning information, then use single neuron controller to set the parameter so as to realize the intelligent control system. The proposed method is verified, the results show that the control method has faster response time, higher control precision compared with the traditional PID control methods; it is a strong adaptability, robustness and anti-interference ability.
机译:工业控制系统是一个复杂的非线性时变系统,传统的PID控制仅限于线性系统,因此控制效果不理想。为了提高控制精度,提出了一种基于RBF神经网络的控制方法。首先利用RBFNN控制器对离散模型进行辨识,得到PID参数的整定信息,然后使用单神经元控制器进行参数设置,从而实现智能控制系统。实验结果表明,与传统的PID控制方法相比,该控制方法具有更快的响应时间,更高的控制精度。它具有很强的适应性,鲁棒性和抗干扰能力。

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