基于鲁棒自适应滑模观测器的多故障重构

针对一类不确定非线性系统, 基于滑模观测器研究执行器和传感器同时故障时的鲁棒重构问题. 引入线性变换矩阵并添加后置滤波器构建增维系统, 综合??_∞ 控制将鲁棒滑模观测器增益矩阵设计方法, 转化为LMI 约束下的多目标凸优化问题. 在滑模增益中添加了自适应律, 确保状态估计误差渐近稳定, 同时滑模运动经有限时间到达滑模面, 在此基础上给出执行器和传感器故障同时重构算法. 最后通过数值算例表明了所提出方法的有效性.

Design of the robust adaptive sliding mode observer for multiple fault reconstruction

A scheme of robust fault reconstruction via the sliding mode observer(SMO) is proposed, which is used for a class of uncertain nonlinear Lipschitz system with the simultaneous actuator and sensor faults. Firstly, an orthorhombic matrix and a filter are introduced, and the augmented system is constructed, then the gain matrix of the robust SMO is calculated by the multi objective convex optimization under linear matrix inequalities. Meanwhile, an adaptive law is added in the sliding mode gain, to make the state estimated error asymptotic stable, and the sliding mode movement reaches the sliding mode surfaces in the limital time. The reconstructed algorithm is given, which includes both actuator and sensor faults. Finally, an example is presented to illustrate the effectiveness of the proposed approach.