212
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

ON-LINE CONTROLLER TUNING FOR CRITICALLY DAMPED SOPTD SYSTEMS

&
Pages 48-58 | Published online: 04 Sep 2014
 

Abstract

A method is proposed to identify the model parameters of a stable, critically damped second-order plus time delay system. The method uses a step response of the closed-loop system using a PID controller. The two dominant poles of the closed-loop model were obtained using the step response. The process gain was calculated using the steady-state deviation values of the output and the input variable of the process. Using the identified dominant poles in the derived closed-loop characteristic equations, the relevant two nonlinear algebraic equations were derived to calculate the process delay and time constant. Three simulation examples were considered to show the effectiveness of the proposed method. The open-loop and as well as the closed-loop responses of the process were compared with those of the identified model and of the controller design based on the models. A significant improvement was obtained in the performance of the critically damped SOPTD model over that of the FOPTD model. The identified model parameters by the present method were compared with those of the relay auto-tuning method. A simulation study on a nonlinear bio reactor is also reported.

Notes

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/gcec.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,086.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.