Multi-Innovation Stochastic Gradient Identification Algorithm for Hammerstein Controlled Autoregressive Autoregressive Systems Based on the Key Term Separation Principle and on the Model Decomposition

Table 2

The MISG parameter estimates and errors.

𝑡	𝑎1	𝑎2	𝑏1	𝑏2	𝛾1	𝛾2	𝛾3	𝑐1	𝑐2	𝛿 (%)
100	1.79885	0.80074	0.49998	0.65013	0.99968	0.50004	0.24953	0.21240	0.36032	7.46185
200	1.79813	0.80153	0.49999	0.65014	0.99955	0.50000	0.24927	0.37423	0.25902	3.87441
500	1.79820	0.80154	0.50001	0.65020	0.99927	0.49994	0.24876	0.32965	0.06371	5.69751
1000	1.79998	0.79973	0.50000	0.65023	0.99910	0.49990	0.24844	0.32849	0.19041	1.23012
2000	1.79979	0.79992	0.50000	0.65023	0.99909	0.49990	0.24842	0.28734	0.20472	0.55706
3000	1.79989	0.79982	0.50000	0.65023	0.99909	0.49990	0.24842	0.28556	0.20496	0.62823
True values	1.80000	0.80000	0.50000	0.65000	1.00000	0.50000	0.25000	0.30000	0.20000