Adaptive Critic Designs and their Implementations on Different Neural Network Architectures

Jung Wook Park; G. K. Venayagamoorthy; Ronald G. Harley

Adaptive Critic Designs and their Implementations on Different Neural Network Architectures

Jung Wook Park, G. K. Venayagamoorthy, Ronald G. Harley

Department of Electrical and Electronic Engineering

Research output: Contribution to conference › Paper › peer-review

5 Citations (Scopus)

Abstract

The design of nonlinear optimal neurocontrollers based on the Adaptive Critic Designs (ACDs) family of algorithms has recently attracted interest. This paper presents a summary of these algorithms, and compares their performance when implemented on two different types of artificial neural networks, namely the multilayer perceptron neural network (MLPNN) and the radial basis function neural network (RBFNN). As an example for the application of the ACDs, the control of synchronous generator on an electric power grid is considered and results are presented to compare the different ACD family members and their implementations on different neural network architectures.

Original language	English
Pages	1879-1884
Number of pages	6
Publication status	Published - 2003
Event	International Joint Conference on Neural Networks 2003 - Portland, OR, United States Duration: 2003 Jul 20 → 2003 Jul 24

Other

Other	International Joint Conference on Neural Networks 2003
Country/Territory	United States
City	Portland, OR
Period	03/7/20 → 03/7/24

All Science Journal Classification (ASJC) codes

Software
Artificial Intelligence

Cite this

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title = "Adaptive Critic Designs and their Implementations on Different Neural Network Architectures",

abstract = "The design of nonlinear optimal neurocontrollers based on the Adaptive Critic Designs (ACDs) family of algorithms has recently attracted interest. This paper presents a summary of these algorithms, and compares their performance when implemented on two different types of artificial neural networks, namely the multilayer perceptron neural network (MLPNN) and the radial basis function neural network (RBFNN). As an example for the application of the ACDs, the control of synchronous generator on an electric power grid is considered and results are presented to compare the different ACD family members and their implementations on different neural network architectures.",

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AU - Venayagamoorthy, G. K.

AU - Harley, Ronald G.

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AB - The design of nonlinear optimal neurocontrollers based on the Adaptive Critic Designs (ACDs) family of algorithms has recently attracted interest. This paper presents a summary of these algorithms, and compares their performance when implemented on two different types of artificial neural networks, namely the multilayer perceptron neural network (MLPNN) and the radial basis function neural network (RBFNN). As an example for the application of the ACDs, the control of synchronous generator on an electric power grid is considered and results are presented to compare the different ACD family members and their implementations on different neural network architectures.

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M3 - Paper

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T2 - International Joint Conference on Neural Networks 2003

Y2 - 20 July 2003 through 24 July 2003

ER -

Adaptive Critic Designs and their Implementations on Different Neural Network Architectures

Abstract

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All Science Journal Classification (ASJC) codes

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