Adaptive Neural Network Control of Thermoacoustic Instability in Rijke Tube: A Fully Actuated System Approach  

作　　者：ZHAO Yuzhuo MA Dan MA Hongwei 

机构地区：[1]State Key Laboratory of Synthetical Automation for Process Industries and College of Information Science and Engineering,Northeastern University,Shenyang 110819,China [2]College of Information Science and Engineering,Northeastern University,Shenyang 110819,China

出　　处：《Journal of Systems Science & Complexity》2022年第2期586-603,共18页系统科学与复杂性学报（英文版）

基　　金：This research was supported by the National Natural Science Foundation of China under Grant No.61973060;the Science Center Program of National Natural Science Foundation of China under Grant No.62188101.

摘　　要：Thermoacoustic instability phenomena often encounter in gas turbine combustors,especially for the premixed combustor design,with many possible detrimental results.As a classical experiment,the Rijke tube is the simplest and the most effective illustration to study the thermoacoustic instability.This paper investigates the active control approach of the thermoacoustic instability in a horizontal Rijke tube.What’s more,the radial basis function(RBF)neural network is adopted to estimate the complex unknown continuous nonlinear heat release rate in the Rijke tube.Then,based on the proposed second-order fully actuated system model,the authors present an adaptive neural network controller to guarantee the flow velocity fluctuation and pressure fluctuation to converge to a small region of the origin.Finally,simulation results demonstrate the feasibility of the design method.

关 键 词：Adaptive neural network control fully actuated system nonlinear system Rijke tube thermoacoustics instability 

分 类 号：TK471[动力工程及工程热物理—动力机械及工程] TP183[自动化与计算机技术—控制理论与控制工程]