NARMA-L2 Controller for Five-Area Load Frequency Control
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TLDR
The load-frequency control (LFC) based on neural network for improving power system dynamic performance is investigated and the controller is adaptive and is based on a nonlinear auto regressive moving average (NARMA-L2) algorithm.Abstract:
This paper investigates the load-frequency control (LFC) based on neural network for improving power system dynamic performance. In this paper an Artificial Neural Network (ANN)based controller is presented for the Load Frequency Control (LFC) of a five area interconnected power system. The controller is adaptive and is based on a nonlinear auto regressive moving average (NARMA-L2) algorithm . The working of the conventional controller and ANN based NARMA L2 controllers is simulated using MATLAB/SIMULINK package . . The Simulink link results of both the controllers are compared.read more
Citations
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Proceedings ArticleDOI
Application of NARMA L2 controller for load frequency control of multi-area power system
Dhanesh Kumar Sambariya,V. Nath +1 more
TL;DR: In this paper study of automatic load frequency control is carried out for a multi-area power system using an intelligent controller and NARMA-L2 controller is used for investigating the dynamic response of the frequency and Tie-line power in the interconnected area.
Journal ArticleDOI
Control of Continuous Stirred Tank Reactor using Neural Networks
Normah Abdullah,Tan Ching Yee,Azah Mohamed,Mohd Marzuki Mustafa,Mohd. Haniff Osman,Abu Bakar Mohamad +5 more
TL;DR: The simulation results show the superiority of the NARMA-L2 in accurately tracking the composition set-point changes in the CSTR and control the system better as compared to that of the conventional PID.
Journal ArticleDOI
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
TL;DR: The goal of this work is to employ the structure of the Modified Elman Neural Network model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems.
Journal ArticleDOI
A Non-Linear Controller for Forecasting the Rising Demand for Electric Vehicles Applicable to Indian Road Conditions
S Poorani,Murugan R +1 more
TL;DR: This paper is to implement & develop the idea of short term load forecasting by using Artificial Neural Network, the design of the neural network model, input data selection and Training & Testing by using shortterm load forecasting will be described in paper.
Proceedings ArticleDOI
Modeling and Simulation of A Photovoltaic Cell Module Controlled with Nonlinear Autoregressive Moving Average-L2 Controller
TL;DR: This research paper includes simulations for the design of single-diodes solar cells under the influence of different temperatures and saturation conditions to demonstrate the efficacy of the solar cell.
References
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TL;DR: An adaptive fuzzy gain scheduling scheme for conventional PI and optimal load frequency controllers and a Sugeno type fuzzy inference system is used in the proposed controller.
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