面向变后掠过程的飞行器智能抗扰动控制  

Intelligent Anti-disturbance Control of Flight Vehicle for Variable-sweep Process

作　　者：卢家乐 梁小辉 LU Jiale;LIANG Xiaohui(School of Automation,Northwestern Polytechnical University,Xi’an 710129,China)

机构地区：[1]西北工业大学自动化学院,西安710129

出　　处：《宇航学报》2024年第12期1997-2008,共12页Journal of Astronautics

基　　金：国家自然科学基金(62203357);航空科学基金(202300130530);中央高校科研业务费专项(G2023KY05101)。

摘　　要：针对变后掠飞行器变形过程中复杂气动变化造成的控制系统跟踪性能下降问题,提出了一种基于执行依赖启发式动态规划(ADHDP)的主动抗扰动控制方法,保证变形过程稳定的同时优化了系统的跟踪精度。首先,考虑飞行器变后掠过程中的模型不确定和严重外部扰动,结合扰动观测和反步控制的思想,设计了一种基于自适应神经网络的基础控制器,确保了飞行器在变后掠过程中能够对给定信号稳定控制。然后,将基础控制系统的跟踪误差作为状态量输入执行-评价网络进行在线学习,近似获得最优补偿控制输入,消除了变形过程的气动变化和未建模动态对跟踪性能的影响,进一步提升了变后掠飞行器闭环控制系统的跟踪性能。最后,通过仿真分析证明了所设计控制方法的有效性和优越性。To address the issue of decreased tracking performance of the control system caused by complex aerodynamic changes during the morphing process of variable-sweep flight vehicle,an active disturbance rejection control method based on action-dependent heuristic dynamic programming is proposed.This method ensures the stability of the morphing process while optimizing the tracking accuracy of the system.Initially,a basic controller utilizing adaptive neural networks is designed to handle model uncertainties and severe external disturbances during the deformation process.This controller,based on disturbance observation and backstepping control method,ensures stable control of the flight vehicle during the morphing process.Subsequently,the tracking error of the basic control system is used as the state input for an action-critic network,which conducts online learning to approximate the optimal compensation control input.This approach eliminates the impact of aerodynamic changes and unmodeled dynamics on tracking performance,thereby enhancing the overall tracking performance of the closed-loop control system of the variable-sweep flight vehicle.Simulation analysis is conducted to validate the effectiveness and superiority of the proposed control method.

关 键 词：变后掠飞行器 抗扰动控制 自适应动态规划 神经网络 扰动观测器 

分 类 号：V249.7[航空宇航科学与技术—飞行器设计]