基于模糊深度置信网络的陶瓷梭式窑PID优化控制

PID Optimization Control Based on Fuzzy Depth Belief Network for Ceramic Shuttle Kiln

针对目前陶瓷梭式窑控制方法落后的情况,本文提出了一种基于模糊深度置信网络的陶瓷梭式窑PID参数优化控制方法。同时,设计了模糊深度置信网络结构模型,给出了所设计的控制器结构和相应的算法,并通过改进的LM算法来估计网络参数,从而降低样本数据训练时的存储空间和计算复杂度。该方法通过采集实时温度数据以及使用模糊深度置信网络在线自适应调整PID控制器参数对陶瓷梭式窑温度进行控制。最后,将该方法应用于陶瓷梭式窑模型进行仿真实验来验证控制效果。仿真结果表明,所设计的控制器比传统的PID控制器使得系统跟踪梭式窑理想温度最大绝对误差减少了19%,因而本文提出的方法是有效的和可行的。

In view of the backward control method of ceramic shuttle kiln at present,a PID parameter optimization control method based on fuzzy depth confidence network is proposed in this work.At the same time,the model of fuzzy depth belief network is designed,while the structure of the controller and the corresponding algorithm are provided.The improved LM algorithm is used to estimate the network parameters to reduce the sample data storage space and computational complexity.In this method,the temperature of ceramic shuttle kiln is controlled by collecting real-time temperature data and on-line adaptive adjusting PID controller parameters with the fuzzy depth belief network.Finally,the method is applied to the ceramic shuttle kiln model to verify the control effect.As compared with the traditional PID controller,the controller designed in this study results in the maximum absolute error of tracking the shuttle kiln ideal temperature reduced by 19%.Therefore,the method proposed in this paper is effective and feasible.