抄録
A new control method of nonlinear dynamic systems is proposed based on the impulse responses of universal learning networks (ULNs). ULNs form a superset of neural networks. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. One of the distinguished features of the proposed control method is that the impulse response of the systems is considered as an extended part of the criterion function and it can be calculated by using the higher order derivatives of ULNs. By using the impulse response as the criterion function, nonlinear dynamics with not only quick response but also quick damping and small steady state error can be more easily obtained than the conventional nonlinear control systems with quadratic form criterion functions of state and control variables.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 362-372 |
| ページ数 | 11 |
| ジャーナル | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics |
| 巻 | 31 |
| 発行部数 | 3 |
| DOI | |
| 出版物ステータス | Published - 2001 6 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence
- Human-Computer Interaction
これを引用
A new control method of nonlinear systems based on impulse responses of universal learning networks. / Hirasawa, Kotaro; Furuzuki, Takayuki; Murata, Junichi; Jin, Chunzhi.
：: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 巻 31, 番号 3, 06.2001, p. 362-372.研究成果: Article
}
TY - JOUR
T1 - A new control method of nonlinear systems based on impulse responses of universal learning networks
AU - Hirasawa, Kotaro
AU - Furuzuki, Takayuki
AU - Murata, Junichi
AU - Jin, Chunzhi
PY - 2001/6
Y1 - 2001/6
N2 - A new control method of nonlinear dynamic systems is proposed based on the impulse responses of universal learning networks (ULNs). ULNs form a superset of neural networks. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. One of the distinguished features of the proposed control method is that the impulse response of the systems is considered as an extended part of the criterion function and it can be calculated by using the higher order derivatives of ULNs. By using the impulse response as the criterion function, nonlinear dynamics with not only quick response but also quick damping and small steady state error can be more easily obtained than the conventional nonlinear control systems with quadratic form criterion functions of state and control variables.
AB - A new control method of nonlinear dynamic systems is proposed based on the impulse responses of universal learning networks (ULNs). ULNs form a superset of neural networks. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. One of the distinguished features of the proposed control method is that the impulse response of the systems is considered as an extended part of the criterion function and it can be calculated by using the higher order derivatives of ULNs. By using the impulse response as the criterion function, nonlinear dynamics with not only quick response but also quick damping and small steady state error can be more easily obtained than the conventional nonlinear control systems with quadratic form criterion functions of state and control variables.
KW - Higher order derivatives
KW - Impulse responses
KW - Nonlinear control
KW - Nonlinear system
KW - Universal learning networks
UR - http://www.scopus.com/inward/record.url?scp=0035359948&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0035359948&partnerID=8YFLogxK
U2 - 10.1109/3477.931521
DO - 10.1109/3477.931521
M3 - Article
C2 - 18244799
AN - SCOPUS:0035359948
VL - 31
SP - 362
EP - 372
JO - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SN - 1083-4419
IS - 3
ER -