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Stable linearization using multilayer neural networks (1996)
Conference Proceeding
Delgado, A., Kambhampati, C., & Warwick, K. (1996). Stable linearization using multilayer neural networks. . https://doi.org/10.1049/cp%3A19960551

The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedbac... Read More about Stable linearization using multilayer neural networks.

The relative order of a class of recurrent networks (1994)
Conference Proceeding
Manchanda, S., Kambhampati, C., Tham, M., & Green, G. (1994). The relative order of a class of recurrent networks. . https://doi.org/10.1049/cp%3A19940266

Three types of recurrent network configurations have been proposed since they enable adequate description of temporal behaviour. The concept of relative order has been introduced so as to provide a framework for analysing such network configurations.... Read More about The relative order of a class of recurrent networks.

Approaches to the optimizing control problem (1988)
Journal Article
Ellis, J. E., Kambhampati, C., Sheng, G., & Roberts, P. D. (1988). Approaches to the optimizing control problem. International Journal of Systems Science, 19(10), 1969-1985. https://doi.org/10.1080/00207728808964092

The selection of the steady-state controls which enable a system to operate in an optimum manner is the optimizing control problem. An examination of direct and adaptive model-based approaches to this problem is made. In the direct approach, system m... Read More about Approaches to the optimizing control problem.