Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
|
 |
RBFN-based decentralized adaptive control of a class of large-scale non-affine nonlinear systems
| |
|
Original Article
RBFN-based decentralized adaptive control of a class of large-scale non-affine nonlinear systems
Tong Zhao1 
| (1) |
Department of Automatic Control, Qingdao University of Science and Technology, Qingdao, China |
Received: 31 January 2007 Accepted: 24 April 2007 Published online: 22 May 2007
Abstract For a class of large-scale decentralized nonlinear systems with strong interconnections, a radial basis function neural network
(RBFN) adaptive control scheme is proposed. The system is composed of a class of non-affine nonlinear subsystems, which are
implicit function and smooth with respect to control input. Based on implicit function theorem, inverse function theorem and
the design idea of pseudo-control, a novel control algorithm is proposed. Two neural networks are used to approximate unknown
nonlinearities in the subsystem and unknown interconnection function, respectively. The stability is proved rigidly. The result
of simulation validates the effectiveness of the proposed scheme.
Keywords Decentralized control - Adaptive control - RBFN - Non-affine - Large-scale nonlinear system
Fulltext Preview (Small, Large)
 References secured to subscribers.
|
|
|
|
|
|