An efficient on-line thermal input estimation method using kalman filter and recursive least square algorithm

摘要

An on-line thermal unknown's estimation method using Input Estimation algorithm has been successfully employed in 1-D and 2-D Inverse Heat Conduction Problems (IHCP). However, implementing this method involves handling various system parameters such as measurement noise, modeling error, external disturbance and changes due to time variation. In this work, we use Root Mean Square Error (RMSE) as performance index, versus forgetting factor under input numerical experiment to identify not only the performance surface, but also the optimal or robust forgetting factor. To directly synthesize Kalman filter with input estimator, this work also presents an efficient robust forgetting factor zone, capable of providing a reasonable tracking time-lag and noise filtered estimation results. In addition, the thermal diffusion lag caused by the diffusion nature of the IHCP is also discussed and compensated for.