论文信息 - RBF neural networks base on particle swarm optimization and its application in control system of flatness and gauge

RBF neural networks base on particle swarm optimization and its application in control system of flatness and gauge

The automatic flatness control and automatic gauge control (AFC-AGC) is a complex system with strong nonlinear coupling and large time delay. With the requirement of further enhancement of product quality, putting forward decoupling control of strip shape and thickness is urgent. So in this paper, the decoupling control based on adaptability of the Radical is Basis Function (RBF) neural network, together with an on-line learning algorithm based on process optimum are proposed with good performances of decoupling and robustness.

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