<![CDATA[Conveyor belt systems are essential components in industrial automation, but controlling their speed accurately is a significant challenge. Classic PID controllers, while common, struggle to handle the inherent nonlinearities of these systems, such as varying friction and sudden load changes. The adaptive Fuzzy-PID controller, which auto-tunes its parameters, has been proposed as a superior alternative. However, most existing research is limited to software simulations, leaving a gap between theoretical performance and practical, real-world applicability. This paper addresses this gap by presenting the complete design, construction, and experimental verification of a Fuzzy-PID controller implemented on a physical conveyor belt model. The methodology includes system identification via multi-sine input to extract a baseline transfer function, followed by the deployment of the control algorithm on an embedded Arduino Nano microcontroller. Experimental results are presented and directly compared with those of a conventional PID controller to evaluate its performance. Quantitative findings confirm that the embedded Fuzzy-PID controller provides superior performance, reducing the rise time to 0.16 s (from 0.20 s) and significantly decreasing the settling time to 0.56 s (a 48.1% improvement over the PID's 1.08 s). Furthermore, the steady-state error was reduced by 36.4%, demonstrating its superior stability and efficiency in a practical hardware environment and confirming its feasibility for industrial applications.]]>
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