执行器故障不确定非线性系统最优自适应输出跟踪控制

本文针对一类具有执行器故障的多输入多输出（Multi-input multi-output，MIMO）不确定连续仿射非线性系统，提出了一种最优自适应输出跟踪控制方案.设计了保证系统稳定性的不确定项估计神经网络权值调整算法，仅采用评价网络即可同时获得无限时域代价函数和满足哈密顿-雅可比-贝尔曼（Hamilton-Jacobi-Bellman，HJB）方程的最优控制输入.考虑执行器卡死和部分失效故障，设计最优自适应补偿控制律，所设计的控制律可以实现对参考输出的一致最终有界跟踪.飞行器控制仿真和对比验证表明了本文方法的有效性和优越性.

Optimal Adaptive Output Tracking Control for a Class of Uncertain Nonlinear Systems With Actuator Failures

An optimal adaptive actuator failure output tracking control scheme is proposed for a class of multi-input multi-output (MIMO) uncertain affine nonlinear continuous-time systems with redundant actuators subject to uncertain failures. The weight adjustment law of the neural network uncertainty estimators can guarantee the stability of the control system, and only critic neural network is used in the proposed adaptive dynamic programming (ADP) scheme to simultaneously get the infinite horizon cost function and the approximate optimal control input satisfying the Hamilton-Jacobi-Bellman (HJB) equation. Considering the stuck-in-space and loss of effectiveness faults of actuators, an optimal adaptive compensation control scheme is designed, which can guarantee the uniformly ultimate boundedness tracking ability of the closed loop system. Flight control simulations and comparative analysis results have demonstrated the effectiveness and advantage of the proposed method.