本文针对线性定常离散系统提出了一种有效的基于输出残差的自适应状态估计方法。
In this paper, based on output residuals, an efficient adaptive state estimation approach is presented for linear time-invariant discrete system.
系统辨识是基于免疫RBF神经网络，用于故障检测的残差是通过对系统的模型输出与系统的实际输出的在线比较得到的。
The system identification is based on immune strategy RBFNN, and the residuals are generated by on-line comparing the system model outputs with the actual system outputs.
使用训练好的SVR模拟系统的动态特性，并将输出结果和实际系统输出相比较，从而生成故障残差。
After being trained, SVR is used to simulate system dynamic characteristic. The simulation result is compared with actual output, and then fault error is drawn.
应用推荐