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Entry  Sun Oct 7 23:39:10 2012, Den, Update, Modern Control, state estimation est_time.pngest_freq.pdf
    Reply  Mon Oct 8 09:51:30 2012, rana, Update, Modern Control, state estimation 
       Reply  Mon Oct 8 12:34:52 2012, Den, Update, Modern Control, state estimation 
Message ID: 7497     Entry time: Sun Oct 7 23:39:10 2012     Reply to this: 7499
Author: Den 
Type: Update 
Category: Modern Control 
Subject: state estimation 

I've applied online state estimation technique using Kalman filter to LQG controller. It helps to estimate states that we do not measure. I've considered MC2 local damping, we measure position and want to estimate velocity that we need for control. We can either differentiate the signal or apply state estimation to avoid huge noise injection at high frequencies. In state estimation we need to know noise covariance, I've assumed that LID sensor noise is 0.1 nm. Though covariance can be calculated better.

In the time-domain figure C1:SUS-MC2_SUSPOS_IN1 = MC2 postion, C1:SUS-MC2_SUSPOS_OUT = MC2 velocity obtained by differentiation, 2 other channels are estimations of position and velocity.

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