基于神经网络的非线性系统轨迹线性化自适应容错控制

针对一类仿射非线性系统，首先采用轨迹线性化方法将其等价表示为线性时变系统；然后利用神经网络构建伪逆模型以及动态故障模型：最后基于模型参数变化，应用李亚普诺夫稳定性理论构建标称系统控制器及故障补偿控制律，从而实现系统故障下的稳定有界容错控制．仿真结果表明了所提出算法的有效性．

Adaptive fault-tolerant control of nonlinear systems using trajectory linearization based on neural network

Aiming at a class of affine nonlinear system, a trajectory linearization method is used to equivalently transform the
nonlinear system into a linear time-varying(LTV) system. Then, a pseudo-inverse and a fault dynamic model are established
by using neural network. Finally, the nominal controller and the fault accommodation laws are established by using the
Lyapunov method from parameter variety. Thus the stability of the fault-suffered system is ensured. Simulation results show
the effectiveness of the proposed algorithm.