Data-Driven Adaptive Fuzzy-PID Control of TITO Coupled Tank System with Input Delay: Design, Implementation, and Performance Evaluation

Coupled tank systems have been commonly employed across various industries to maintain accurate liquid levels in storage tanks. However, the dynamic nature and input–output reactions within TITO-coupled tank systems pose challenges for controller design. Possible enhancement towards accurate controlling of TITO systems through the application of the existing PID controller has been recognized. A data-driven Adaptive Fuzzy-PID controller is designed in this article for improved control accuracy of TITO systems. Safe Experimental Dynamics (SED) is employed as the data-driven tool to determine optimal Fuzzy-PID parameters that minimize control tracking performance and errors. The proposed method achieved effective Adaptive Fuzzy-PID parameter adjustments in the absence of the layout’s mathematical modeling. An integrated approach between Fuzzy logic and PID control demonstrated significant potential for enhanced control performance over conventional PID controllers. Through simulation results, the proposed objective function has been demonstrated to yield superior control accuracy. The integration of data-driven techniques and utilization of the Adaptive Fuzzy-PID controller offers promising prospects in advancing the control performance of TITO-coupled tank systems.