Adaptive Neural Fault-Tolerant Control of a 3-DOF Model Helicopter System
Adaptive Neural Fault-Tolerant Control of a 3-DOF Model Helicopter System
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DOI：
10.1109/tsmc.2015.2426140
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发表时间：
2016-02
期刊：
影响因子：
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通讯作者：
Mou Chen;P. Shi;C. Lim
中科院分区：
文献类型：
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作者：
Mou Chen;P. Shi;C. Lim
本文针对三自由度模型直升机，在系统不确定性、未知外部干扰和执行器故障的情况下，提出了一种自适应神经容错控制方案。针对系统不确定性和执行器非线性故障，提出了一种基于径向基函数神经网络的扰动观测器。将未知的外部干扰和未知的神经网络逼近误差作为一个复合干扰，由另一个非线性干扰观测器进行估计。基于扰动消除器的自适应神经元容错控制方案，然后开发跟踪期望的系统输出存在的系统不确定性，外部干扰，和执行器故障。利用李雅普诺夫方法分析了整个闭环系统的稳定性，保证了所有闭环信号的收敛性。最后，仿真结果表明了新的控制设计技术的有效性。
In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle system uncertainty and nonlinear actuator faults, a neural network disturbance observer is developed based on the radial basis function neural network. The unknown external disturbance and the unknown neural network approximation errors are treated as a compound disturbance that is estimated by another nonlinear disturbance observer. A disturbance observer-based adaptive neural fault-tolerant control scheme is then developed to track the desired system output in the presence of system uncertainty, external disturbance, and actuator faults. The stability of the whole closed-loop system is analyzed using the Lyapunov method, which guarantees the convergence of all closed-loop signals. Finally, the simulation results are presented to illustrate the effectiveness of the new control design techniques.