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Tabl e 2.
The FF-SG estimates and errors
t α
1
α
2
α
3
α
4
α
5
δ
(%)
100 0.1174 0.0619 0.8128 0.9035 -0.1812 20.0681
200 0.1927 0.1290 0.9055 1.0303 -0.1449 9.0010
300 0.2224 0.1689 0.8981 1.0440 -0.1097 5.7755
500 0.2285 0.1994 0.9009 1.0734 -0.1009 3.4647
1000 0.2206 0.2145 0.9003 1.0762 -0.1026 2.2923
1500 0.2105 0.2298 0.8962 1.0786 -0.1004 1.0502
2000 0.2033 0.2333 0.8983 1.0778 -0.1023 0.5736
2500 0.1952 0.2395 0.8952 1.0825 -0.0981 0.5179
3000 0.1980 0.2361 0.8958 1.0754 -0.1055 0.6487
True values 0.2000 0.2400 0.9000 1.0800 -0.1000
5 Conclusions
An approach to identify Hammerstein systems with piece-wise linearity is pre-
sented in this paper. The model of the nonlinear system be turned into an
identification model by using a switching function, then based on the identifica-
tion model, we proposed an SG algorithm and an FF-SG algorithm to estimate
all the parameters of the system. The simulation results verify the proposed
algorithm.
References
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