Back to Search
Start Over
Multiple Model Adaptive Control for a Class of Linear-Bounded Nonlinear Systems.
- Source :
-
IEEE Transactions on Automatic Control . Jan2015, Vol. 60 Issue 1, p271-276. 6p. - Publication Year :
- 2015
-
Abstract
- This study proposes a novel multiple model adaptive control (MMAC) algorithm for a class of nonlinear discrete time systems. The controller consists of a linear indirect adaptive controller, a nonlinear indirect adaptive controller based on neural networks, and a switching mechanism. The control input is generated by the switching mechanism, which selects the candidate controller from the two controllers. The assumption of the nonlinear term is relaxed to linear-bounded when a modified adaptive law is introduced. The restraint that the nonlinear term of the plant should be linear with respect to the control input is removed by resorting to the pole-placement control scheme. The proposed control method can address the properties of non-minimum phase and open-loop instability in the linear part of the plant. The proposed MMAC algorithm can guarantee the bounded-input-bounded-output stability of the proposed closed-loop switching system. A simulation example is presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 00189286
- Volume :
- 60
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Automatic Control
- Publication Type :
- Periodical
- Accession number :
- 100151052
- Full Text :
- https://doi.org/10.1109/TAC.2014.2323161