Output details
13 - Electrical and Electronic Engineering, Metallurgy and Materials
University of Manchester : B - Electrical and Electronic Engineering
Article title
An ILC-Based Adaptive Control for General Stochastic Systems With Strictly Decreasing Entropy
Type
D - Journal article
Title of journal
IEEE Transactions on Neural Networks
Article number
-
Volume number
20
Issue number
3
First page of article
471
ISSN of journal
1045-9227
Year of publication
2009
URL
-
Number of additional authors
2
Additional information
To measure the randomness of closed-loop systems, existing stochastic control methods use variance, which inherently assumes that the random variables are Gaussian, conflicting with most practical situations. In this work, entropy was used as a general measure for randomness and a new control strategy developed that minimises entropy for general nonlinear and non-Gaussian unknown stochastic systems. This work has been taken up by several research groups e.g. in Greece (DOI: 10.1109/TNN.2010.2076302) in the design of a neuro-adaptive force/position control, and in China (DOI:10.3390/e15010032) on stochastic controller design.
Interdisciplinary
-
Cross-referral requested
-
Research group
8 - Control Systems
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
