基于降维观测器和超螺旋算法的执行器故障重构方法

Actuator Fault Reconstruction Method Based on Reduce-order Observer and Super-twisting Algorithm

  • 摘要: 针对一类具有执行器故障的不确定非线性系统, 对执行器故障和未知干扰同时重构方法进行了讨论. 首先,对原系统进行等价状态变换和输出变换, 从而设计出能直接消除系统执行器故障和未知干扰的降维观测器,以对系统状态进行渐近收敛估计; 在此基础上,提出一种可以对未知信息进行重构的方法.然后,基于超螺旋算法, 给出了系统输出微分的估计,达到了执行器故障和未知干扰同时重构的目的. 最后,对一个实例进行仿真,仿真结果表明了该方法的有效性.

     

    Abstract: For a class of uncertain nonlinear systems with actuator faults, the problems of actuator fault and unknown disturbance simultaneous reconstruction are discussed. Firstly, a kind of equivalent transformation method for state and output of original system is introduced, and then a reduced-order observer which can eliminate the influences of actuator fault and unknown disturbance directly is developed to get the asymptotical convergence estimation of original system states. A method to reconstruct unknown information is proposed based on the reduced-order observer. Secondly, the estimated derivatives of system outputs are obtained based on the super-twisting algorithm, and the purpose of simultaneous reconstruction for actuator faults and unknown disturbances is reached. Finally, a numerical simulation example is given to show the effectiveness of the proposed methods.

     

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