基于自适应神经网络的非线性飞控系统设计

将动态逆理论、神经网络和自适应控制相结合应用于非线性飞行控制系统设计中，通过动态逆控制律将非线性耦合系统转换为线性解耦系统，采用具有在线学习能力的神经网络来补偿反馈线性化中存在的逆误差，最后利用李亚普诺夫稳定性理论推导了在线网络权值的自适应调整规则。仿真结果表明，这种控制结构具有良好的跟踪能力和极强的鲁棒性。

Design of Nonlinear Flight Control System Using Adaptive Neural Network

The methods which based on the dynamic inversion theory, neural network theory and adaptive control theory, are applied to design the nonlinear flight control system. The nonlinear system are transformed into linear system by dynamic inversion law. The feedback linearization error is compensated by neural network which is capable of on-line learning. A stable weights adjustment rule is derived using a Lyapunov function. Simulation results demonstrate that the control structure has good tracking performance and robustness.