The issue of composite adaptive exponential tracking control for a class of large-scale nonlinear systems under model uncertainties, external disturbances, along with multiplicative and additive time-varying sensor faults is considered in this paper. The command filtered backstepping approach is employed to address the “explosion of terms” issue inherent in standard backstepping method. A novel compensating system is incorporated to mitigate the effects of filtering errors and enhance the convergence of tracking errors. The composite estimation laws are designed by integrating the compensated tracking errors, prediction errors stemming from output estimators, along with the proportional and integral estimation errors of faulty terms. This on-line estimation framework enables achieving fast, robust and accurate estimation, even when employing low learning and modification gains. By incorporating modification terms with appropriate time-varying gains, it is demonstrated that the resulting system is globally exponentially stable. Finally, the effectiveness of the presented FTC approach is illustrated through two simulation examples.

中文翻译：

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传感器故障大规模非线性系统的复合自适应指数跟踪控制

本文考虑了一类大规模非线性系统在模型不确定性、外部干扰以及乘性和加性时变传感器故障下的复合自适应指数跟踪控制问题。命令过滤反步方法用于解决标准反步方法中固有的“术语爆炸”问题。采用新颖的补偿系统来减轻滤波误差的影响并增强跟踪误差的收敛性。复合估计法则是通过集成补偿跟踪误差、输出估计器产生的预测误差以及错误项的比例和积分估计误差来设计的。即使采用较低的学习和修改增益，该在线估计框架也能够实现快速、稳健和准确的估计。通过将修改项与适当的时变增益相结合，证明了所得系统是全局指数稳定的。最后，通过两个仿真示例说明了所提出的 FTC 方法的有效性。