Back to Search
Start Over
New quasi-Newton iterative learning control scheme based on rank-one update for nonlinear systems.
- Source :
- Journal of Supercomputing; Mar2014, Vol. 67 Issue 3, p653-670, 18p
- Publication Year :
- 2014
-
Abstract
- This paper develops an algorithm for iterative learning control on the basis of the quasi-Newton method for nonlinear systems. The new quasi-Newton iterative learning control scheme using the rank-one update to derive the recurrent formula has numerous benefits, which include the approximate treatment for the inverse of the system's Jacobian matrix. The rank-one update-based ILC also has the advantage of extension for convergence domain and hence guaranteeing the choice of initial value. The algorithm is expressed as a very general norm optimization problem in a Banach space and, in principle, can be used for both continuous and discrete time systems. Furthermore, a detailed convergence analysis is given, and it guarantees theoretically that the proposed algorithm converges at a superlinear rate. Initial conditions which the algorithm requires are also established. The simulations illustrate the theoretical results. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09208542
- Volume :
- 67
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Journal of Supercomputing
- Publication Type :
- Academic Journal
- Accession number :
- 94629515
- Full Text :
- https://doi.org/10.1007/s11227-013-0960-5