An Adaptive Control with FAHV Being at Convergence on Specified Time Based on Event Triggering Mechanism and Minimum Learning Parameter
LI Jiangmiao
SHAO Xingling
XU Yuemei
DENG Ruixiang
Abstract：Aimed at the problems that the results of current adaptive control for Flexible Air-breathing Hypersonic Vehicle(FAHV)are capable of only achieving asymptotic error convergence to the preset en-velope,and the problems of computational explosion and excessive occupancy of airborne resources remain due to online updating of neural weights,an adaptive control method is proposed for FAHV specified time convergence based on event triggering mechanism and minimum learning parameters.Firstly,an improved preset performance control mechanism is proposed which does not depend on the exact initial error value and can ensure the convergence of the specified error time.Secondly,a relative threshold event-triggered neural network for FAHV interference identification is constructed.Finally,a control algorithm of relative threshold event triggering is designed,which is capable of effectively reducing the consumption of commu-nication resources of the closed-loop controller,and achieving good control accuracy on the basis of non-isoperiodic signal transmission.The simulation results show that the proposed method can track the height/speed reference signal on a specified time under conditions of low computing and transmission re-source consumption.
Keywords：flexible air-breathing hypersonic vehicleimproved default performance controlrelative threshold events trigger neural networksrelative threshold events trigger control
Publication Date：2024-04-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：14( 48-61 )