Simple analytic rules for model reduction and PID controller tuning

1.8kCitations
Citations of this article
344Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The aim of this paper is to present analytic rules for PID controller tuning that are simple and still result in good closed-loop behavior. The starting point has been the IMC-PID tuning rules that have achieved widespread industrial acceptance. The rule for the integral term has been modified to improve disturbance rejection for integrating processes. Furthermore, rather than deriving separate rules for each transfer function model, there is a just a single tuning rule for a first-order or second-order time delay model. Simple analytic rules for model reduction are presented to obtain a model in this form, including the "half rule" for obtaining the effective time delay. © 2002 Elsevier Science Ltd. All rights reserved.

References Powered by Scopus

Internal Model Control: Pid Controller Design

1432Citations
N/AReaders
Get full text

Design of PI controllers based on non-convex optimization

488Citations
N/AReaders
Get full text

Tuning PI Controllers for Integrator/Dead Time Processes

383Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Revisiting the Ziegler-Nichols step response method for PID control

888Citations
N/AReaders
Get full text

An overview of control performance assessment technology and industrial applications

475Citations
N/AReaders
Get full text

Handbook of PI and PID controller tuning rules

311Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Skogestad, S. (2003). Simple analytic rules for model reduction and PID controller tuning. Journal of Process Control, 13(4), 291–309. https://doi.org/10.1016/S0959-1524(02)00062-8

Readers over time

‘10‘11‘12‘13‘14‘15‘16‘17‘18‘19‘20‘21‘22‘23‘24‘25015304560

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 158

68%

Researcher 36

16%

Professor / Associate Prof. 28

12%

Lecturer / Post doc 10

4%

Readers' Discipline

Tooltip

Engineering 186

76%

Chemical Engineering 32

13%

Computer Science 15

6%

Energy 12

5%

Article Metrics

Tooltip
Social Media
Shares, Likes & Comments: 3

Save time finding and organizing research with Mendeley

Sign up for free
0