Fuzzy-Optimized model reference adaptive control of interacting and noninteracting processes based on MIT and Lyapunov rules

Various system parameter variations occur during operations in several existing process industries. These result shifts, thus, requiring adequate control strategies to compensate for these alterations, which consequently maintain desired response. A paradigm is the coupled tank systems; such systems, level and flow of liquid must be adequately controlled reaction equilibrium as well avoid spillage or equipment damage. The model reference adaptive (MRAC) an strategy that creates a law, subject adaptation gain, causes system’s plant continuously track until zero tracking error achieved. Massachusetts Institute Technology (MIT) Lyapunov approaches were used develop mechanism, adjust parameters law. Conventionally, fixed value adopted gain; however, adaption gain can also determined heuristically. fuzzy logic was optimally determine thus results fuzzy-optimized MRAC (FOMRAC) system. Consequently, schemes comparatively analysed two-tank arranged noninteracting interacting fashions. Using MATLAB/Simulink, depicted FOMRAC systems had faster settling times comparison with systems. Overall, based on rule yielded lowest performance indices values. In addition, scheme completely eliminated overshoot resulted from implementation other process.