Ethiopia Institute of Technology- Mekelle

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Author: search.filters.author.Ybrah Zemcheal

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    Design of an Adaptive Neuro-Fuzzy Inference System Controller for Temperature and Concentration Control in a MIMO Continuous Stirred Tank Reactor (CSTR)
    (Mekelle University, 2025-04-07) Ybrah Zemcheal
    The Continuous Stirred Tank Reactor (CSTR) is a critical unit in chemical processing industries, where precise control of process variables is essential for optimal product quality and efficiency. Among the key variables, temperature and concentration are particularly important to regulate. However, chemical processes often exhibit nonlinear and multivariable behavior, making conventional controllers less effective in real-time operation (PID control in CSTR exhibits sluggish or oscillatory responses for feed concentration, slow response to variable water flow, Poor robustness for uncertain parameters (e.g., reaction rates, heat transfer coefficients), perform poorly due to cross-coupling effects, less nonlinearity handling due to reaction kinetics. Challenges such as dynamic process variations, reactant nonlinearities, fluctuating environmental conditions, and diverse disturbances further complicate control. Additionally, most industrial chemical processes are multi-input multi-output (MIMO) systems, necessitating advanced control strategies and decoupling techniques. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed as an advanced control approach to enhance system performance and accuracy compared to conventional controllers. ANFIS integrates the structured knowledge representation of fuzzy logic with the adaptive learning capabilities of neural networks, offering improved control for complex systems. The performance of ANFIS is evaluated against a traditional PID controller through offline simulations using MATLAB/Simulink. The results demonstrate that ANFIS outperforms PID control in key performance metrics, including overshoot, rise time, settling time, and system stability. Furthermore, ANFIS exhibits superior disturbance rejection capabilities, making it a more robust solution for CSTR control in industrial applications.