Extended Closed Loop Output Error Method

This method has been developed in order to identify without bias "plant + disturbance" models corresponding to extended closed loop output error structure . It will then give unbiased estimations only for processes which are only affected by filtered white disturbances.

For this method a recursive parameter adaptation algorithm is considered as follows:

e°(t+1) = y(t+1)-qT(t)f(t)

F-1(t+1) = F-1(t)+lf(t)fT(t)

q(t+1) =q(t)+F(t+1)f(t)e°(t+1)

where e°(t+1) is the a priori closed loop prediction error, q(t) is the vector of the parameters of the plant model (B/A) and of the noise model H(q-1), f(t) is the regressor vector containing the previous values of the input of the adjustable plant model û(t) and of the predictor output and of the a posteriori prediction error filtered by 1/S (ef(t+1)=e(t+1)/S). F(t) is the adaptation gain and l is the forgetting factor.

See: Closed loop identification module .

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(file xcloe.htm)