针对存在执行器故障的一类仿射非线性系统, 基于自适应动态规划方法, 提出了一种新型的容错控制器。利用故障观测器估计执行器故障, 并利用故障信息构建一个改进型的性能指标函数, 将容错控制问题转化为最优控制问题。同时使用策略迭代(PI)算法, 通过构造评价神经网络来求解HJB方程, 获得近似最优容错控制律, 并且基于李雅普诺夫函数, 证明该容错控制器可以确保闭环系统渐近稳定。最后, 通过仿真验证了该方法的有效性

A novel Fault Tolerant Control (FTC) scheme is developed based on Adaptive Dynamic Programming (ADP) for a class of affine nonlinear systems with actuator failures. The estimated actuator failure from a fault observer is utilized to construct an improved performance index function, so the FTC problem can be transformed into an optimal control problem. By using Policy Iteration(PI)algorithm, the Hamilton-Jacobi-Bellman equation can be solved by constructing a critic neural network. Then, the approximate optimal controller can be derived directly. The closed-loop system is guaranteed to be asymptotically stable via the Lyapunov stability theorem. Finally, an example is presented to demonstrate the effectiveness of the proposed method.