Output details
11 - Computer Science and Informatics
University of Plymouth
Article title
Adaptive Predictive Control Using Neural Network for a Class of Pure-feedback Systems in Discrete-time
Type
D - Journal article
Title of journal
IEEE Transactions on Neural Networks
Article number
9
Volume number
19
Issue number
-
First page of article
1599-161
ISSN of journal
1045-9227
Year of publication
2008
URL
-
Number of additional authors
2
Additional information
<24> This paper overcomes the noncausal problem in discrete-time controller design and significantly reduces the complexity of the conventional step-by-step backstepping design. The study also demonstrates superior performance over other methods in the literature, resulting in a very high citation count. This simplified design approach has inspired (see citations by Liu, 2010, 2011; Park, 2009). It has also significantly impacted the further development of approximation based predictive control (Zhang, 2010) with application to motor systems and SMA actuators.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
57
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
