Closed Loop Output Error Method

This method has been developed in order to identify without bias "plant + disturbance" models corresponding to closed loop output error structure . It will then give unbiased estimations only if the noise is independent with respect to the plant input and to the external excitation.

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, 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. F(t) is the adaptation gain and l is the forgetting factor.

See: Closed loop identification module .

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(file cloe.htm)