Robust neural network tracking controller based on simultaneous perturbation stochastic approximation
the robust neural controller based on the SPSA has been developed to obtain the guaranteed stability with a normalized learning algorithm. A three-layered neural network is used for the simulation study with 30 hidden layer neurons and two output neurons, which was trained by the standard back-propa...
Saved in:
Main Author: | Kyaw, Minn Latt. |
---|---|
Other Authors: | Song, Qing |
Format: | Theses and Dissertations |
Published: |
2008
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/4539 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Similar Items
-
A robust recurrent simultaneous perturbation stochastic approximation training algorithm for recurrent neural networks
by: Xu, Zhao, et al.
Published: (2013) -
A robust recurrent simultaneous perturbation stochastic approximation training algorithm for recurrent neural networks
by: Song, Qing, et al.
Published: (2014) -
Simultaneous perturbation stochastic approximation based neural networks for online learning
by: Choy, M.C., et al.
Published: (2014) -
Robust neural controller for robot manipulator
by: Lou, Jia Ming
Published: (2011) -
Design of a robust adaptive neural tracking controller
by: Nay Lin Tun
Published: (2008)