一类不确定性离散非线性重复过程的迭代学习容错控制

Iterative Learning Fault-tolerant Control for a Class of Uncertain Nonlinear Discrete Repetitive Processes

  • 摘要: 针对一类具有非线性和执行器故障的重复运行不确定离散系统,提出了一种迭代学习鲁棒容错控制算法.首先通过定义执行器故障系数矩阵,将迭代学习控制过程转化为等价形式的不确定性非线性重复过程模型,然后基于混合李亚普若夫函数方法讨论非线性重复过程在时间轴和批次轴两个维度上的稳定性,并以线性矩阵不等式形式给出鲁棒容错控制器存在的充分条件和设计方法,同时保证系统正常和执行器故障情形下系统的容错稳定性能.最后,单杆机械手系统的输出跟踪控制仿真结果验证了本文算法的有效性.

     

    Abstract: For a class of uncertain discrete repetitive systems with nonlinearity and actuator faults, we propose an iterative learning fault-tolerant control algorithm. First, we transform the iterative learning control process into an equivalent uncertain nonlinear repetitive process model by defining an actuator fault coefficient matrix. Then, we discuss the stability of the nonlinear repetitive process on time and trial axes, based on the mixed Lyapunov function method, and provide the sufficient condition for the stability of the repetitive control system in terms of the linear matrix inequality technology. The fault-tolerant performance of the system can be guaranteed both in normal and failure actuator conditions. The simulation results of the output tracking of a single-link manipulator system reveal the effectiveness of the algorithm.

     

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