A fractional order parallel control structure tuned with meta-heuristic optimization algorithms for enhanced robustness

This paper studies an improved fractional order parallel control structure (FOPCS) for enhancing the robustness in an industrial control loop having a first order process with dead time along with its tuning aspects. Since inclusion of fractional order calculus also increase the number of parameters...

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Bibliographic Details
Published in:Journal of Electrical Engineering Vol. 70; no. 1; pp. 16 - 24
Main Authors: Goyal, Vishal, Mishra, Puneet, Shukla, Aasheesh, Deolia, Vinay Kumar, Varshney, Aarti
Format: Journal Article
Language:English
Published: Bratislava Sciendo 01.02.2019
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Subjects:
Calculus
Computer simulation
Controllers
fractional order calculus
Heuristic methods
meta-heuristic optimization algorithms
Optimization
parallel control structure
Parameters
Performance evaluation
PID controller
Robust control
Robustness
Search algorithms
Tuning
ISSN:1339-309X, 1335-3632, 1339-309X
Online Access:Get full text
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Summary:This paper studies an improved fractional order parallel control structure (FOPCS) for enhancing the robustness in an industrial control loop having a first order process with dead time along with its tuning aspects. Since inclusion of fractional order calculus also increase the number of parameters to be determined for a particular control loops, tuning becomes an essential task. Four different tuning methods are considered to optimize the gains of parallel control structure (PCS) and FOPCS. Integral of time weighted absolute error for servo and regulatory problems along with overshoot value have been considered for performance evaluation. Extensive simulation studies including change in setpoint and mismatch in processmodel parameters have been carried out. On the basis of these studies, it was observed that FOPCS tuned by backtracking search algorithm, outperformed all other controllers in terms of considered performance measures.
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ISSN:1339-309X
1335-3632
1339-309X
DOI:10.2478/jee-2019-0002