Robust Adaptive Fault-Tolerant Control for a Class of Unknown Nonlinear Systems
Robust Adaptive Fault-Tolerant Control for a Class of Unknown Nonlinear Systems
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DOI：
10.1109/tie.2016.2595481
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发表时间：
2017
影响因子：
7.7
通讯作者：
Jinxi Zhang;Guang‐Hong Yang
中科院分区：
文献类型：
--
作者：
Jinxi Zhang;Guang‐Hong Yang
研究了一类严格反馈非线性系统在执行器故障和外部干扰下的容错跟踪控制问题。除了控制方向之外，执行器故障、非线性和外部干扰的先验知识是完全未知的。基于反推方法，自适应容错控制方案的开发，而不使用神经网络。在控制设计中，提出了一组新的反馈机制来补偿未知的系统动态和执行器故障。此外，为了放宽对系统初始状态的要求，设计了一种修改技术，以在短时间内调整参考信号和虚拟控制律。结果表明，该方法保证了闭环系统的全局稳定性，并具有良好的跟踪性能。通过对单连杆机械手和船舶自动驾驶仪的仿真，说明了上述结果。
This paper studies the fault-tolerant tracking control problem for a class of strict-feedback nonlinear systems subjected to actuator faults and external disturbances. The prior knowledge for actuator fault, nonlinearity, and external disturbance is totally unknown, besides the control directions. Based on a backstepping approach, an adaptive fault-tolerant control scheme is developed, without utilizing neural networks. In the control design, a group of new feedback mechanisms are proposed to compensate for the unknown system dynamics and actuator faults. Furthermore, to relax a requirement of the initial system states, a modification technique is designed to adjust the reference signal and virtual control laws for a short time. It is shown that the global closed-loop stability is guaranteed and the tracking performance is achieved. The above result is illustrated via simulations on a one-link manipulator and a ship autopilot.