Model-free adaptive optimal design for trajectory tracking control of rocket-powered vehicle

作     者：Wenming NIE Huifeng LI Ran ZHANG Wenming NIE;Huifeng LI;Ran ZHANG

作者机构：School of AstronauticsBeihang UniversityBeijing 100083China Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation TechnologiesMinistry of EducationBeijing 100083China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2020年第33卷第6期

页      面：1703-1716页

核心收录：

学科分类：080703[工学-动力机械及工程] 082502[工学-航空宇航推进理论与工程] 08[工学] 0807[工学-动力工程及工程热物理] 0825[工学-航空宇航科学与技术] 

基　　金：supported by the National Key R&D Program of China(No.2016YFB1200100) 

主　　题：Adaptive dynamic program­ming Dynamic neural network Model-free Solid-rocket-powered vehi­cle Trajectory tracking 

摘      要：An adaptive optimal trajectory tracking controller is presented for the Solid-RocketPowered Vehicle(SRPV)with uncertain nonlinear non-affine dynamics in the framework of adaptive dynamic ***,considering that the ascent model of the SRPV is non-affine,a model-free Single Network Adaptive Critic(SNAC)method is developed based on the dynamic neural network and the traditional SNAC *** developed model-free SNAC method overcomes the limitation of the traditional SNAC method that can only be applied to affine ***,a closed-form adaptive optimal controller is designed for the non-affine dynamics of *** controller can adjust its parameters under different flight conditions and converge to the approximate optimal controller through online ***,the convergence to the approximate optimal controller is *** theoretical analysis of the uniformly ultimate boundedness of the tracking error is also *** results demonstrate the effectiveness of the proposed controller.