Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1708261 | Applied Mathematics Letters | 2013 | 6 Pages |
Abstract
Since the stochastic gradient algorithm has a slower convergence rate, this letter presents a multi-innovation stochastic gradient algorithm for a class of dual-rate sampled systems with preload nonlinearity. The basic idea is to transform the dual-rate system model into an identification model which can use dual-rate data by using the polynomial transformation technique. A simulation example is provided to verify the effectiveness of the proposed method.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Jing Chen, Lixing Lv, Ruifeng Ding,