International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 18, No. 1, 8 Feb. 2026
Cover page and Table of Contents: PDF (size: 1319KB)
Parameter Optimisation of Type 1 and Interval Type 2 Fuzzy Logic Controllers for Performance Improvement of Industrial Control System
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Author(s)
Index Terms
Fuzzy Logic Level Control, Design of Type 1 and Interval Type 2 FLC, Genetic Algorithms, Parameter Optimisation, Simulation
Abstract
The fuzzy logic controllers (FLC) gain popularity in ensuring stable and high-performance control of nonlinear industrial plants with no reliable model, where the traditional controllers fail. Their standard expert-based design and simple algorithms that meet the demands for fast execution and economical use of computational resources ease their implementation into programmable logic controllers for wide industrial real-time control applications. This research presents a novel approach to enhancing the performance of FLC systems by compensating for the subjectivity inherent in expert-based design through optimization of the parameters of type-1 (T1) and interval type-2 (IT2) PID FLC membership functions (MF) using genetic algorithms. The approach is demonstrated for controlling the solution level in a carbonization column for soda ash production. Simulations reveal that optimization improves the system performance, measured by a newly introduced overall performance indicator for dynamic accuracy, robustness, and control smoothness, by 48% for the T1 FLC system and 30% for the IT2 FLC system. No improvement is observed in the substitute of T1 MF by IT2 MF for both the empirically designed and the optimised FLC.
Cite This Paper
Desislava R. Stoitseva-Delicheva, Snejana T. Yordanova, "Parameter Optimisation of Type 1 and Interval Type 2 Fuzzy Logic Controllers for Performance Improvement of Industrial Control System", International Journal of Intelligent Systems and Applications(IJISA), Vol.18, No.1, pp.62-74, 2026. DOI:10.5815/ijisa.2026.01.05
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