一类非线性系统的H2容错控制器的设计及其在空间飞行器的应用

针对存在执行器故障的不确定系统,本文研究了一种H2鲁棒容错控制的设计.控制器包括三个功能: 1)利用径向基函数(Radial basis function, RBF)神经网络估计得到的近似非线性函数构成闭环控制,抵消系统的非线性特征; 2)能实现H2性能指标的最优控制; 3)利用滑模控制抑制模型估计误差以提高控制精度, 并且控制器具有指定稳定裕度的设计功能.文中提出了用于执行器故障估计的调整规则, 故障估计信息用于控制律的设计.基于Lyapunov函数,推导了满足H2最优性能的充分条件:非线性二次矩阵不等式. 为了降低计算成本,给出了不等式求解的简化算法,避免了在线求解非线性矩阵不等式.通过一个空间飞行器模型的仿真, 验证了本文提出方法的有效性.

H2 Fault Tolerant Controller Design for a Class of Nonlinear Systems with a Spacecraft Control Application

This paper presents an H₂ robust fault tolerant controller design method for uncertain systems in the presence of unknown failures. The developed H₂ controller with optimal index incorporates a neural network learning action and sliding mode control action. A radial basis function (RBF) neural network is utilized to approximate the unknown nonlinear dynamics. An updating rule is designed to estimate actuator failure. The sliding-mode control is used to eliminate the effect of neural network approximation error. Based on Lyapunov function, the sufficient condition for H₂ optimal performance is developed in terms of nonlinear quadratic matrix inequality. In order to reduce computing cost, a simplification algorithm is developed, which avoids solving on-line nonlinear matrix inequality. A numerical example on a spacecraft system is presented to demonstrate the effectiveness of the proposed methods.