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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
IPD and FLC results are compared in terms of current, voltage and velocity for reference input.
📌 3 Key Takeaways
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Objective & Hypothesis:In this study, IPD and Fuzzy Logic Controller (FLC) are applied separately to perform velocity control of the system that has two degree of freedom in real time.
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Key Findings & Data:IPD controller uses coefficients which are integral, differential and proportional are calculated with Coefficient Diagram Method (CDM).
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Conclusion & Impact:IPD and FLC results are compared in terms of current, voltage and velocity for reference input.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:IPD · FLC · CDM
Abstract
In this study, IPD and Fuzzy Logic Controller (FLC) are applied separately to perform velocity control of the system that has two degree of freedom in real time. IPD controller uses coefficients which are integral, differential and proportional are calculated with Coefficient Diagram Method (CDM). This method is based on polynomial approach and has many advantages such as easy design procedure, an interpretation of settling time, stability and parameter tuning. FLC uses linguistic variables and can be applied easily. IPD and FLC results are compared in terms of current, voltage and velocity for reference input.
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Cite This Article
AVCU, A. (2018). Comparison of IPD and Fuzzy Logic Velocity Control In Two Degree of Freedom DC Motor System. International Journal of Engineering Science and Application, Cilt: 2 - Sayı: 1, 1–7. https://ajindex.com/articles/832913