基于自适应神经网络的飞行器主动容错控制  

Active Fault Tolerant Control of Aircraft Based on Adaptive Neural Networks

作　　者：黄海洋 韩渭辛 HUANG Haiyang;HAN Weixin(School of Automation,Northwestern Polytechnical University,Xi'an 7100129)

机构地区：[1]西北工业大学自动化学院,西安710129

出　　处：《飞控与探测》2024年第1期8-13,共6页Flight Control & Detection

基　　金：航空科学基金(2020000505053004,20200005053003,201905053005,20180753007);陕西省重点研发计划(2021GXLH-01-13);中国科协青年托举人才计划(2022QNRC001)。

摘　　要：针对飞行器非线性系统执行器故障,利用RBF神经网络和自适应控制律,提出了基于自适应神经网络的故障重构和容错控制方法。设计了自适应神经网络观测器,利用神经网络逼近故障,引入调节因子,设计自适应律以在线调整神经网络权重向量和中心向量。构造自适应神经网络控制器,结合神经网络设计补偿控制输入。利用Lyapunov稳定性定理证明了所提方法可以实现系统渐近稳定。仿真实验结果验证了所提的方法对故障系统具有良好的观测性能、控制精度和响应速度。For linear systems with nonlinear terms and faults,a fault diagnosis and fault-tolerant control method based on adaptive neural networks is proposed by using RBF neural networks and adaptive laws.First,an adaptive neural network observer is designed to approximate the fault,and an adaptive law is designed to adjust the neural network weight vector and center vector online with a regulator introduced.Second,the adaptive neural network controller was designed,and the compensating control input is designed in conjunction with the neural network.Then,the proposed method is proved to achieve asymptotic stability of the system using the Lyapunov stability theorem.Finally,the simulation experimental results verify that the proposed method has good observation performance,control accuracy,and response speed for the faulty system.

关 键 词：飞行器 故障重构 容错控制 自适应神经网络 观测器 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置] TP277[自动化与计算机技术—控制科学与工程]