Interval type-2 fuzzy PID controllers with interval of confidence and various types of footprints of uncertainty

This study introduces the notion of interval of confidence (IoC) for the modeling of fuzzy controllers and presents three novel mathematical models of interval type-2 fuzzy proportional-integral-derivative (IT2FPID) controllers by utilizing the concept of IoC and various types of footprints of uncertainty (FoUs) having parallelogram, bottom-wide triangle, and top-wide triangle shapes. The properties and computational aspects of the proposed controllers are analyzed mainly in terms of IoCs and FoUs. All the developed controllers with various types of FoUs are plant-model-free nonlinear controllers with variable gains and structures. It is proved that more generalized models of IT2FPID controllers can be attained by replacing the fuzzy singletons with IoCs. The suitability of introducing IoC in IT2FPID controllers is verified by showing that IoC does not play any role in the mathematical modeling of type-1 (T1) fuzzy PID controllers. To demonstrate the effectiveness of the proposed controllers, extensive simulation studies and numerical and hardware experiments are conducted. The simulation and experimental results affirm the proposed controllers' superiority over conventional and fuzzy PID ones, opening up new possibilities for improved performance in real-world control applications. • Introduces the notion of IoC for the modeling of IT2FPID controllers. • Three new models of IT2FPID controllers are unveiled. • Properties and computational burdens of the controllers are discussed. • Theoretical developments are validated via numerical and hardware experiments. • Effectiveness of the controllers is shown by means of extensive comparisons.

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Institutions

Publication Details

Journal
Information Sciences
Published
2024-12-24
DOI
https://doi.org/10.1016/j.ins.2024.121795
Citations
5
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
1.74

Funders

Controls
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article

Interval type-2 fuzzy PID controllers with interval of confidence and various types of footprints of uncertainty

Jung–Min Yang, Manoranjan Praharaj, Debdoot Sain, B.M. Mohan
5 citations
Information Sciences
Fuzzy Logic and Control Systems
1.74
article

Interval type-2 fuzzy PID controllers with interval of confidence and various types of footprints of uncertainty

Jung–Min Yang, Manoranjan Praharaj, Debdoot Sain, B.M. Mohan
article en
5 citations

Abstract

This study introduces the notion of interval of confidence (IoC) for the modeling of fuzzy controllers and presents three novel mathematical models of interval type-2 fuzzy proportional-integral-derivative (IT2FPID) controllers by utilizing the concept of IoC and various types of footprints of uncertainty (FoUs) having parallelogram, bottom-wide triangle, and top-wide triangle shapes. The properties and computational aspects of the proposed controllers are analyzed mainly in terms of IoCs and FoUs. All the developed controllers with various types of FoUs are plant-model-free nonlinear controllers with variable gains and structures. It is proved that more generalized models of IT2FPID controllers can be attained by replacing the fuzzy singletons with IoCs. The suitability of introducing IoC in IT2FPID controllers is verified by showing that IoC does not play any role in the mathematical modeling of type-1 (T1) fuzzy PID controllers. To demonstrate the effectiveness of the proposed controllers, extensive simulation studies and numerical and hardware experiments are conducted. The simulation and experimental results affirm the proposed controllers' superiority over conventional and fuzzy PID ones, opening up new possibilities for improved performance in real-world control applications. • Introduces the notion of IoC for the modeling of IT2FPID controllers. • Three new models of IT2FPID controllers are unveiled. • Properties and computational burdens of the controllers are discussed. • Theoretical developments are validated via numerical and hardware experiments. • Effectiveness of the controllers is shown by means of extensive comparisons.

Information SciencesVol. 699
Indian Institute of Technology Kharagpur (IN), Kyungpook National University (KR)
Ministry of Education, National Research Foundation of Korea
Climate action
Openalex Percentile: Top 12%
Fuzzy Logic and Control Systems
1.74
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