Regularized Least Squares Recursive Algorithm with Forgetting Factor for Identifying Parameters in the Grinding Process

Table 4

Identification results of 10 experiments.

Parameters
Truth value	−1.5	1	1.5	1
RLSRAFF	−1.5009	0.9989	1.4985	0.9958
RLSM [31]	−1.4965	0.9984	1.4874	1.0582
LSM [30]	−1.5039	1.0044	1.5852	0.8855
LSRAFF [30]	−1.4980	0.9938	1.4812	0.9872
Truth value	−1.0	0.8	3.0	4.0
RLSRAFF	-0.9963	0.7996	2.9921	3.9940
RLSM [31]	−1.0191	0.8023	2.9365	3.8294
LSM [30]	−1.1040	0.8143	3.1093	3.7783
LSRAFF [30]	−1.0048	0.8054	3.0474	4.0382
Truth value	−0.9	0.3	2.0	3.0
RLSRAFF	−0.9037	0.3017	2.0170	2.9730
RLSM [31]	−0.9058	0.3175	2.0299	2.9587
LSM [30]	−0.9306	0.3233	1.9454	3.1175
LSRAFF [30]	−0.9257	0.3096	1.9708	3.0338
Truth value	−0.5	0.1	4.0	10.0
RLSRAFF	−0.4989	0.1008	3.9981	9.9925
RLSM [31]	−0.5128	0.0959	3.9381	9.9606
LSM [30]	−0.4790	0.0945	3.8541	9.9446
LSRAFF [30]	−0.4885	0.0948	4.1090	10.0459
Truth value	−0.1	0.4	10.0	7.0
RLSRAFF	−0.1021	0.4020	9.9249	6.9556
RLSM [31]	−0.0857	0.3694	9.8860	6.9263
LSM [30]	−0.0798	0.4077	10.0263	7.0824
LSRAFF [30]	−0.1077	0.3979	9.8964	6.8515
Truth value	−0.8	1.0	−2.0	6.0
RLSRAFF	−0.8015	0.0010	−2.0104	5.9948
RLSM [31]	−0.8013	0.9965	−1.8112	5.9769
LSM [30]	−0.8022	1.0106	−1.9778	6.1568
LSRAFF [30]	−0.8020	1.0003	−1.9851	5.9752
Truth value	−0.7	0.4	2.0	−3.0
RLSRAFF	−0.7011	0.4016	2.0014	−2.9984
RLSM [31]	−0.7157	0.3897	1.9152	−2.9785
LSM [30]	−0.6705	0.3668	1.8951	−3.0987
LSRAFF [30]	−0.7381	0.3899	2.1158	−2.9857
Truth value	−0.6	−0.2	−4.0	−3.0
RLSRAFF	−0.6060	−0.1988	−4.0408	−3.0135
RLSM [31]	−0.6247	−0.1962	−3.9870	−2.9425
LSM [30]	-0.6309	-0.1755	-4.0537	−2.8846
LSRAFF [30]	−0.5882	−0.2156	−3.9819	−2.9502
Truth value	0.3	0.4	8.0	5.5
RLSRAFF	0.3004	0.4006	7.9987	5.4976
RLSM [31]	0.2921	0.3982	7.9762	5.5475
LSM [30]	0.2834	0.3877	7.8914	5.3927
LSRAFF [30]	0.2895	0.3989	8.0239	5.4837
Truth value	0.3	−0.5	−3.0	1.0
RLSRAFF	0.2935	−0.4956	−3.0148	0.9929
RLSM [31]	0.3283	−0.4890	−2.9772	0.9802
LSM [30]	0.2553	−0.5161	−2.8933	1.0424
LSRAFF [30]	0.2621	−0.5128	−3.0151	1.0201