本文就武装直升机大机动、高敏捷性神经网络鲁棒自适应飞行控制系统的设计问题展开研究。
The robust adaptive flight control system design with neural network of attack helicopter is studied in this dissertation and super maneuver nimble of attack helicopter is realized.
考虑到飞行控制系统闭环反馈及实时的特性，设计了多个鲁棒自适应观测器用于传感器的故障隔离与重构。
Based on performance of real-time and closed loop feedback flight control system, a set of robust adaptive observers are set up for sensor fault isolation and reconfiguration.
本文主要研究了闭环控制系统的故障检测和基于故障检测的自适应重构控制在飞行控制系统中的应用。
We mainly research on fault detection of closed-loop control systems and adaptive reconfiguration control based on fault detection and its application on flight control systems.
结果表明利用该方法设计的飞行控制系统在跟踪参考输入信号时具有较好的自适应跟踪性能和鲁棒性能。
The result showed that the flight control system designed by this method has fine adaptive tracking performance and robustness when following the reference input signals.
最近，大量的模拟研究揭示了一个基于神经网络的方法，直接自适应控制在飞行控制系统的设计带来的潜在利益。
Numerous simulation studies have recently revealed the potential benefits of a neural network-based approach to direct adaptive control in the design of flight control systems.
为了方便设计六自由度的飞行控制系统，引入了带有约束指令滤波的自适应退步控制算法。
The results show that the proposed control system works well in this case, and performs better than other PID controllers.
为了方便设计六自由度的飞行控制系统，引入了带有约束指令滤波的自适应退步控制算法。
The results show that the proposed control system works well in this case, and performs better than other PID controllers.
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