Data Filtering Based Recursive Least Squares Algorithm for Two-Input Single-Output Systems with Moving Average Noises

Table 1

The parameter estimates and their errors (𝜎²=0.50², 𝛿_ns=59.70%).

Algorithms	𝑡	𝑎1	𝑎2	𝑏11	𝑏12	𝑏21	𝑏22	𝑑1	𝛿 (%)
F-RLS	100	0.49783	0.82362	0.47259	0.33889	0.45701	0.67571	−0.31256	10.87062
	200	0.53237	0.83678	0.42607	0.30153	0.50390	0.70802	−0.26142	13.33636
	500	0.51680	0.83056	0.43167	0.29518	0.50208	0.66555	−0.35787	6.59957
	1000	0.50285	0.81789	0.42489	0.28951	0.50703	0.61872	−0.35247	4.41100
	2000	0.50405	0.81391	0.42283	0.27871	0.49694	0.62908	−0.38038	3.56288
	3000	0.50565	0.80834	0.41436	0.29579	0.49903	0.62586	−0.39109	2.37173
RELS	100	0.53926	0.86216	0.45846	0.28535	0.44404	0.76552	−0.23374	18.60645
	200	0.54959	0.85622	0.40695	0.27414	0.46667	0.76896	−0.23790	18.13522
	500	0.51636	0.83069	0.42841	0.27674	0.48978	0.67084	−0.38132	6.46314
	1000	0.50859	0.81827	0.42018	0.27842	0.50739	0.62544	−0.36367	4.24112
	2000	0.50723	0.81444	0.42236	0.27730	0.49418	0.62936	−0.38827	3.47473
	3000	0.50794	0.80920	0.41212	0.28907	0.49876	0.62707	−0.39464	2.48087
True values		0.50000	0.80000	0.40000	0.30000	0.50000	0.60000	−0.40000