ISSN : 2583-2646

Fuzzified Control in Band Dryer System

ESP Journal of Engineering & Technology Advancements
© 2024 by ESP JETA
Volume 4  Issue 2
Year of Publication : 2024
Authors : Ajith B Singh, Isthiyaq Ahamed A, Sri Ragavarshini K, Salmanul Faris M
:10.56472/25832646/JETA-V4I2P101

Citation:

Ajith B Singh, Isthiyaq Ahamed A, Sri Ragavarshini K, Salmanul Faris M, 2024. Fuzzified Control in Band Dryer System, ESP Journal of Engineering & Technology Advancements  4(2): 1-10.

Abstract:

Temperature control plays a crucial role in industrial processes that involve air drying. Drying is the process of removing moisture from materials, and the temperature during this process significantly impacts its overall performance. This manuscript proposes a hybrid technique for precise temperature control in band dryer systems, aiming to ensure product quality, process efficiency, and energy conservation. The Proposed Hybrid method is the combined execution of both the Giant Armadillo Optimization (GAO) and fuzzy logic-based PID controller (FL-PID) to optimize temperature control in band dryer systems. Hence, it is named GAO-FL-PID Approach. The proposed GAO algorithm is used to optimize the parameter of the PID controller and FL-PID controller is used to predict the uncertainties within the system. Traditional Proportional-Integral-Derivative (PID) controllers often struggle with the nonlinearities, uncertainties, and disturbances inherent in these systems. This research investigates the application of a fuzzy logic based PID controller to achieve robust and adaptive temperature control in a band dryer system. In this approach, a set of fuzzy rules, based on expert knowledge and process dynamics, dynamically adjusts the PID parameters in real-time based on the temperature error and its rate of change. The hybrid approach combines the strengths of fuzzy logic and PID control, and simulation work is conducted using MATLAB Simulink platform and compared with various existing approaches. The result demonstrates that the adaptive tuning enables the controller to quickly respond to disturbances and maintain tight temperature tracking, minimizing overshoot and settling time. The proposed method shows low settling time of 0.1 S and minimum overshoot of 0.4% compared with other existing methods such as Particle swarm optimization (PSO), Wild horse optimization (WHO), and Seagull Optimization Algorithm (SOA) respectively.

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Keywords:

Temperature Control, Band Dryer System, Fuzzy Logic Controller, Fuzzy-Logic Based PID Controller, Product Quality, Cohen-Coon Method.