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PID controllers have been the most common type of compensators in the past and will continue in the near future. Effort has been taken by researchers to develop simple and systematic way to design these controllers. This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. Recently, it has been revealed the possibility that the fine-tuning method based on Nyquist Stability Criterion has the potential to output a satisfactory closed-loop performance for a given continuous, linear system model. In addition, design of compensator based on Nyquist Stability Criterion is simpler and more robust [3]. On the other hand, Neural Network has become tremendously popular in the control application due to its ability in adaptive learning and approximating function. By implementing Nyquist Stability Criterion's tuning algorithm with Neural Network, this will definitely enhance the process of tuning the PID controller. In this project, the algorithm of the tuning method based on Nyquist Stability Criterion is developed first. Then, data are generated to be used in training the neural network. The NN is used to predict the tuning parameters of PID controller for second order system. The whole project is implemented in MATLAB program. The result obtained in this project has actually showed that the tuning rule based on Nyquist Stability Criterion can fine-tune the PID controller and eventually improve the closed-loop system. Meanwhile the NN model built has been able to predict the parameters for PID controllerat the accuracyof 5%MSE. In the final part of this report, conclusions are drawn and some future work for future development is proposed.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 02 Oct 2013 15:53
Last Modified: 25 Jan 2017 09:46
URI: http://utpedia.utp.edu.my/id/eprint/8114

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