Абстрактный

Model Reference Adaptive Control of Jacketed STIRRED-TANK Heater

Kalpesh B. Pathak, Dipak M. Adhyaru

Paper presents an important adaptive control technique, model reference adaptive control for temperature control in jacketed stirred tank heater. In heater a hot fluid is circulated through the jacket which is assumed to be perfectly mixed. Energy balance equations on the vessel and jacket fluids have been used as a model for simulation. Initially MIT rule technique has been applied for control. Data base of adjustment parameter θ and output of same has been saved for future strategy of neural network learning and training. By applying neural network based algorithm new values of θ have been generated. For uncertain system, results shows that as compared to conventional MRAC, Adjustment parameter θ generated using neural network leads to better result and robustness. Basics of MIT rule and small literature survey on stirred tank jacketed heater control and MRAC has also been discussed.