基于模糊神经网络的络筒机纱线张力控制系统的研究

针对络筒机的纱线张力不稳定性问题,结合模糊系统的鲁棒性、容错性以及神经网络学习能力强的特点,提出了应用模糊神经网络控制器控制纱线张力的方法。开展了纱线张力控制系统、神经网络和模糊控制算法的分析,建立了模糊控制系统和神经网络之间的关系,设计了基于模糊神经网络的纱线张力控制器,应用MATLAB软件仿真验证了基于模糊神经网络的络筒机纱线张力控制系统的可行性。研究结果表明,与线性插值模糊控制效果相比,模糊神经网络控制作用下的系统超调量小,调节时间快,稳定性好,具有一定使用价值。

Research on Yarn Tension Control System of Winder Based on Fuzzy Neural Network

Aiming at the problem of the yarn tension instability of the winder, a new method of fuzzy neural network controller, combined with the robustness and fault tolerance of the fuzzy system and the strong learning capacity of its neural network, was proposed to control yarn tension. The yarn tension control system, the neural network, and the fuzzy control algorithm were analyzed. The relationship between fuzzy control system and neural network was established, and the yarn tension controller based on the fuzzy neural network was designed. The feasibility of yarn tension control system based on fuzzy neural network was verified by applying MATLAB software. The research results showed that the system, compared with the linear interpolation fuzzy control, was valuable with small overshoot, fast settling time, and good stability.