Publikace detail

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

Autoři: Doležel Petr | Mareš Jan

Rok: 2009

Druh publikace: článek ve sborníku

Název zdroje: Proceedings of XXXIVth Seminary ASR 09 Instrument a Control

Název nakladatele: Vysoká škola báňská-Technická univerzita Ostrava

Místo vydání: Ostrava

Strana od-do: 13

Tituly:

Jazyk	Název	Abstrakt	Klíčová slova
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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