基于高斯过程回归的连续式风洞马赫数控制

摘要

Maintaining the stability of Mach number plays an important role in the success of wind tunnel experiments.The traditional PID feedback control algorithm has a certain time lag and can not obtain the required control precision of Mach number in the experiments with continuously changing angle of attack.To overcome this defect,a feed forward strategy based on Gaussian process regression is proposed.The strategy combines the PID controller to carry out the control of Mach number.Firstly,the cleaned data is normalized in addition to cleaning the raw data to reduce the effects of noise.Secondly,the Gaussian process regression is employed to model the relationship between the inputs (angle of attack,real-time Mach number,and cross-sectional area)and the output (rotational speed of compressor)by two different strategies,which randomly divide data set and group data set by Mach number.The trained model is compared with other commonly-used approaches in terms of predictive accuracy.Finally,an improved PID control strategy that leverages the prediction and confidence results of Gaussian process regression is proposed.The experimental results confirm that Gaussian process regression has satisfactory ability of modelling wind tunnel data,and the control strategy that combines the PID with the feed forward control based on Gaussian process regression can improve the control precision of Mach number with continuous variable angles of attack in wind tunnel.%在风洞实验中保持实验段马赫数的稳定对实验的成功具有重要意义.传统的PID控制算法具有一定时滞性,不能满足连续变迎角实验模式下马赫数的控制精度要求.针对这一缺陷,提出了一种基于高斯过程回归的前馈控制策略,结合PID控制器共同完成马赫数控制任务.首先,对原始数据执行了预处理操作,将数据集中的异常数据进行清洗并且对清洗后的数据进行标准化;其次,选取迎角、实时马赫数、实验段截面积作为高斯过程回归模型的输入,压缩机转速作为输出,采用随机划分数据集与分组划分数据集两种策略进行建模,并将高斯过程回归与常用回归模型的预测精度进行了比较;最后,给出了利用高斯过程回归预测结果及预测置信度进行 PID反馈控制的方法.实验结果表明高斯过程回归对风洞实验数据具有很好的建模能力,基于高斯过程回归的前馈控制与 PID结合的控制策略能够提高连续变迎角模式下的马赫数控制精度.