Autors: Ganesh,A., Singh,J.
Title: Adaptive Hybrid Control for Noise Rejection
Keywords: PID controller, Adaptive Neuro-controller, noise rejection

Abstract: System modeling and identification is an important tool for analysis, evaluation and prediction in classification, decision analysis and automatic control.Many models have been suggested for noise rejection.The identification of adaptive controllers for practical system is desired for better control and for improved system response even in the presence of the noise.In this paper,a hybrid controller is developed,using Artificial Neural Network and Genetic algorithm, which can provide adaptation.The neuro-controller translates the data into a control action.A genetic algorithm in integration with neuro-controller is used to determine the weights and biases of the neural network for better response.The performance of these two approaches has been evaluated using data of different plants on a common set of performance indices.The simulations results show that identified GA based Adaptive neuro-controller along with PID controller.

References

    Issue

    9th WSEAS International Conference on NEURAL NETWORKS (NN’08), pp. 100-106, 2008, Bulgaria,

    Вид: публикация в национален форум