Adaptive learning-based optimal tracking control system design and analysis of a disturbed nonlinear hypersonic vehicle model
作者机构:Hypersonic Technology LaboratoryNational University of Defense TechnologyChangsha410073China
出 版 物:《Science China(Technological Sciences)》 (中国科学(技术科学英文版))
年 卷 期:2024年第67卷第6期
页 面:1893-1906页
核心收录:
学科分类:08[工学] 081105[工学-导航、制导与控制] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 080201[工学-机械制造及其自动化]
基 金:supported by the Natural Science Foundation of Hunan Province(Grant No.2021JJ10045) the National Natural Science Foundation of China(Grant No.11972368) the National Key R&D Program of China(Grant No.2019YFA0405300)
主 题:optimal tracking control adaptive dynamic programming RBFNN hypersonic vehicle
摘 要:We propose an adaptive learning-based optimal control scheme for height-velocity control models considering model uncertainties and external disturbances of hypersonic winged-cone *** longitudinal nonlinear model is first established and transformed into the control-oriented error equations,and the control scheme is organized by a steady-compensation *** overcome and eliminate the impact of model uncertainties and external disturbances,an adaptive radial basis function neural network(RBFNN)is designed by a q-gradient *** the height-velocity error system with estimated uncertainties into account,the adaptive learning-based optimal tracking control(ALOTC)scheme is proposed by combining the critic-only adaptive dynamic programming(ADP)framework and parameter optimization of system settling ***,a novel weight update law is proposed to satisfy the online iteration requirements,and the algorithm convergence and closedloop stability are discussed by the Lyapunov ***,four simulation cases are provided to prove the effectiveness,accuracy,and robustness of the proposed scheme for the hypersonic longitudinal control system.