Recursive extended least squares algorithm-based crystallizer ARMAX (Auto Regressive Moving Average Exogenous) model identification method
A technique of least squares and model identification, applied to instruments, adaptive control, control/regulation systems, etc., can solve the problem that ARMAX models cannot achieve parameter estimation
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[0056] Table 1 shows the sampling data of a slab continuous casting machine crystallizer in a steel plant, the sampling time interval Ts = 0.003 seconds, and the number of data points N = 250.
[0057] Select the ARMAX crystallizer model of na=5, nb=3, nc=2;
[0058] Let A(q)=1+a 1 q -1 +a 2 q -2 +a 3 q -3 +a 4 q -4 +a 5 q -5 , B(q)=b 1 q -1 +b 2 q -2 +b 3 q -3 , then the system parameters to be identified are θ ^ 0 = a 1 a 2 a 3 a 4 a 5 b ...
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