基于神经元的喂丝机自适应控制系统

Adaptive Control System of Metal Silk Feeding Machine Based on Neuron

针对喂丝机加工过程工况条件的不定性,利用神经元的自组织自学习能力,提出了一种无需对象建模,易于实现的神经元自适应速度控制系统。仿真结果表明,当系统的参数及环境变化时,相对于PID控制,该神经元控制器具有无超调、无静差、自适应及很强的鲁棒性。

Aiming at the uncertain working conditions during the manufacturing process of metal silk feeding machine and with the utilization of self- organizing and self- learning of neuron, educes a kind of neuron self - adaptation velocity control system with no necessity of object modeling and characterized by easy implementation. The simulation results indicates when the system parameter and circumstance condition change, the neu-ron controller, in contrast with PID control has some characteristics of no static error, no overshoot, self- adaptation and highly robust.