arrow
Return

Controller tuning via performance maps

delete2007-10-01
delete2
PRE
AI
M
Michael J. Piovoso *
J
James J. Alpigini
DOI:10.1016/j.isatra.2004.09.001delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
While there are a number of visual methods common to the design and analysis of dynamic systems, they tend to be specific to their application and limited in the amount of information which they yield. This paper explores a visualization technique, titled the performance map, which is derived from the Julia set commonly used in the visualization of iterative chaos. Performance maps are generated via digital computation, and require a minimum of a priori knowledge of the system under evaluation. By the use of colour-coding, these images convey a wealth of information to the informed user about dynamic behaviours of a system that may be hidden from all but the expert analyst. Application to the tuning of PI controllers is presented. User friendly software makes the application to tuning easy and allows the user to visually inspect any number of potential solutions. The software will be made available upon request. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.
Keywords:
visualization
linear control
PI controller
tuning
dynamics
simulations
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

ISA Transactions cover
ISA Transactions
IF:
6.5
Papers:
5.9K
Citations:
2.0W

Organization

P
Pennsylvania State University
Scholars:
3.0W
Papers: 2.6W
Citations: 7.2W
P
pennsylvania commonwealth system of higher education (pcshe)
Scholars:
12.9W
Papers: 11.7W
Citations: 177
Cited Papers

Cited Papers

System analysis via performance maps
err2003-05-01
err7
PREAI
errAlpigini, JJ; Russell, DW
errShare
errSave
Vestibular rehabilitation by auditory feedback in otolith disorders
err2008-10-01
err0
PREAI
errDietmar Basta; Fabian Singbartl; Ingo Todt; Andrew Clarke; Arne Ernst
errShare
errSave
Iterative feedback tuning: Theory and Applications
err1998-08-01
err675
PREAI
errHjalmarsson, H; Gevers, M; Gunnarsson, S; Lequin, O
errShare
errSave
errShare
errSave
researcher View more