摘要
针对工作环境中存在的干扰和噪声,普通PID控制算法的控制效果较差,提出了一种基于CMAC神经网络与PID控制算法相结合的复合控制算法,通过对结构参数的调整,可以达到较小的误差。仿真结果验证了该算法的有效性,表明这种控制方法能够有效的提高系统的抗干扰性能,并且具有很好的适应性和鲁棒性。
In view of interference and noise existing in the work environment, the effect of ordinary PID control algorithm is poor, the author puts forward a composite control algorithm based on CMAC neural network combining with PID control algorithm. Through the adjustment of structural parameters, it can reach smaller error. The simulation results verify the effectiveness of the algo-rithm, show that this control method can effectively improve the anti-jamming ability of the system. The algorithm has good adapt-ability and robustness.
出处
《自动化与仪器仪表》
2014年第2期34-35,共2页
Automation & Instrumentation
