基于神经元的喂丝机自适应控制系统

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。

Adaptive Control System of Metal Silk Feeding Machine Based on Neuron

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 neuron controller,in contrast with PID control has some characteristics of no static error,no overshoot,self-adaptation and highly robust.