Publication detail

Self-tuning PID Control using Genetic Algorithm and Artificial Neural Networks

Authors: Doležel Petr | Mareš Jan

Year: 2009

Type of publication: článek ve sborníku

Name of source: Proceedings of XXXIVth Seminary ASR 09 Instrument a Control

Publisher name: Vysoká škola báňská-Technická univerzita Ostrava

Place: Ostrava

Page from-to: 13

Titles:

Language	Name	Abstract	Keywords
cze	Nastavování PID regulátoru pomocí genetického algoritmu a umělé neuronové sítě	V článku je prezentována metoda nastavení PID regulátoru pomocí genetického algoritmu a umělé neuronové sítě online.	Genetický algoritmus;umělé neuronové sítě
eng	Self-tuning PID Control using Genetic Algorithm and Artificial Neural Networks	PID controllers are widely used in industry these days due to their useful properties such as simple tuning or robustness. While they are applicable to many control problems, they can perform poorly in some applications. Highly nonlinear system control with constrained manipulated variable can be mentioned as an example. The point of the paper is to string together convenient qualities of conventional PID control and progressive techniques based on Artificial Intelligence. Proposed control method should deal with even highly nonlinear systems. To be more specific, there is described new method of discrete PID controller tuning in this paper. This method tunes discrete PID controller parameters online through the use of genetic algorithm and neural model of controlled system in order to control successfully even highly nonlinear systems. After method description and some discussion, there is performed control simulation and comparison to one chosen conventional control method.	Genetic algorithm;Artifitial neural networks

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