Neural network-based autor-tuning for PID controllers

Title:

Neural network-based autor-tuning for PID controllers

Creator:

Rivas-Echeverría, Francklin, Ríos-Bolívar, Addison, and Casales-Echeverría, Jeanette

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:824ace86-43a7-465e-88a3-f00937211ced
uuid:824ace86-43a7-465e-88a3-f00937211ced

Subject:

PID, neural networks (NN), auto-tuning, and integrál error criteria

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

PID controllers have become the most popular control strategy in indiistrial processes due to tlie versatility and tumiiiig capabilities. The iiicorporation of aiito-tunning tools have increased the use of this kind of controllers. In this paper we i)ropose a neural network-based self-tunning scherne for on-line updating of PID parameters, which is based on integ'ral error criteria (lAE, ISE, ITAE, ITSE).

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2001 Volume:11 | Number:3

Harvested from:

CDK

Metadata only:

false