摘要
为实现风热恒温系统设计,基于无模型自适应控制方法,结合神经网络来对恒温控制系统进行设计。该方法通过RBF神经网络逼近无模型自适应控制器中的参数步长因子和权重因子,并基于梯度下降算法实现其在线自适应整定。仿真研究表明,该方法能够有效处理复杂工业过程中的非线性和随机性问题,为复杂动态系统的自适应控制提供了新的解决方案。
To achieve the wind and thermal constant temperature system,a constant temperature control system based on the model-free adaptive control method combined with neural networks was designed.This method used Radial Basis Function(RBF)neural networks to approximate the step factor and weight factors in the model-free adaptive controller and employed gradient descent algorithms for online adaptive tuning.The simulation results demonstrated that this method could effectively handle nonlinear and stochastic issues in complex industrial processes,providing a new solution for adaptive control of complex dynamic systems.
作者
王鹏鹏
高寨勇
冯文武
WANG Pengpeng;GAO Zhaiyong;FENG Wenwu(Jinxi Group Shanxi Jiangyang Chemical Co.,Ltd.,Taiyuan 030008,Shanxi,China)
出处
《热处理技术与装备》
2025年第2期75-78,共4页
Heat Treatment Technology and Equipment
