Electrical Engineering and Systems Science > Systems and Control
[Submitted on 15 Oct 2022 (v1), last revised 8 Apr 2023 (this version, v3)]
Title:Optimal Controller Tuning Technique for a First-Order Process with Time Delay
View PDFAbstract:We present a controller tuning strategy for first-order plus time delay (FOPTD) processes, where the time delay in the model is approximated using the Padé function. Using Routh-Hurwitz stability analysis, we derive the gain that gives rise to desirable PID controller settings. The resulting PID controller, now correctly tuned, produces satisfactory closed-loop behavior and stabilizes the first-order plant. Our proposed technique eliminates the dead-time component in the model and results in a minimum-phase system with all of its poles and zeros in the left-half $s$-plane. To demonstrate the effectiveness of our approach, we present control simulation results from an in-depth performance comparison between our technique and other established model-based strategies used for the control of time-delayed systems. These results prove that, for the FOPTD model, Padé approximation eliminates the undesirable effects of the time delay and promises a faster tracking performance superior to conventional model-based controllers.
Submission history
From: Clinton Enwerem [view email][v1] Sat, 15 Oct 2022 04:10:19 UTC (137 KB)
[v2] Tue, 25 Oct 2022 08:43:25 UTC (155 KB)
[v3] Sat, 8 Apr 2023 09:18:18 UTC (160 KB)
Current browse context:
eess.SY
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.