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

Table 2

The parameter estimates and their errors (𝜎²=0.10², 𝛿_ns=11.94%).

Algorithms	𝑡	𝑎1	𝑎2	𝑏11	𝑏12	𝑏21	𝑏22	𝑑1	𝛿 (%)
F-RLS	100	0.48293	0.79642	0.41760	0.30069	0.49608	0.58878	−0.40118	1.99087
	200	0.51101	0.81127	0.40743	0.30352	0.50298	0.61790	−0.37052	2.81593
	500	0.50157	0.81012	0.40710	0.29963	0.50121	0.61021	−0.39941	1.17016
	1000	0.49914	0.80525	0.40512	0.29771	0.50204	0.60182	−0.38316	1.35563
	2000	0.50007	0.80429	0.40469	0.29566	0.49964	0.60499	−0.39422	0.78466
	3000	0.49969	0.80258	0.40296	0.29869	0.49998	0.60404	−0.40137	0.43055
RELS	100	0.51462	0.82354	0.41087	0.30152	0.48869	0.64030	−0.14920	18.69550
	200	0.51683	0.81951	0.40067	0.29934	0.49279	0.63819	−0.18953	15.98366
	500	0.50478	0.81270	0.40486	0.29674	0.49758	0.61544	−0.33064	5.07263
	1000	0.50338	0.80708	0.40371	0.29683	0.50111	0.60612	−0.34207	4.35710
	2000	0.50298	0.80552	0.40417	0.29637	0.49871	0.60680	−0.37711	1.81881
	3000	0.50223	0.80344	0.40231	0.29826	0.49969	0.60581	−0.38867	0.98907
True values		0.50000	0.80000	0.40000	0.30000	0.50000	0.60000	−0.40000