Model Reference Adaptive Control and Neural Network-Based Concentration Control of CSTR

The paper discusses the concentration control in Continuous Stirred Tank Reactors (CSTR) using another CSTR as a reference model. The PI controller regulates the reference model, which adjusts the model reference adaptive controller (MRAC). The neural controller is then tuned with the model identified from the second CSTR. The controllers’ performance is assessed through the utilization of MATLAB/SIMULINK aiming to illustrate and enhance the system’s concentration and stability. The simulation results are compared with the Model Reference Adaptive Controller MIT and Lyapunov rules.