Neural Networks for Modelling and Control
Brown, M. and Harris, C.J. (1994) Neural Networks for Modelling and Control. Advances in Intelligent Control Taylor and Francis, 18--55.
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A revival of interest in Artificial Neural Networks has taken place during the past decade. Research has focused on the ability of these algorithms to learn from their past experiences, generalising the stored information so that it affects the network's response for similar inputs. Adaptive and learning systems are attractive to the control engineer as they can offer significant advantages for modelling and controlling time-varying, complex plants operating in non-stationary environments. This chapter provides an introduction to the ANNs which are commonly used in modelling and control applications and compares their advantages and disadvantages. The text is broadly split into three sections which separately describe the network's modelling abilities, the learning rules and the model evaluation strategies.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Additional Information:||Address: London, UK|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||04 May 1999|
|Last Modified:||27 Mar 2014 19:51|
|Publisher:||Taylor and Francis|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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