IMPLEMENTATION OF DC MOTOR SPEED CONTROLLER USING FUZZY LOGIC INTERFACED WITH MICROPROCESSOR

Efficient and precise control of Direct Current (DC) motors is fundamental in various industrial and automation applications, ranging from robotics to conveyor systems, and is crucial for achieving desired operational performance, energy efficiency, and operational safety. This study focuses on the implementation of a DC motor speed control utilizing fuzzy logic, integrated with a microprocessor, to enhance motor control performance. Traditional DC motor speed controllers often fail to provide accurate and precise speed control, especially under varying load conditions. Fuzzy logic control, a powerful nonlinear control approach employing linguistic variables and fuzzy rules, has emerged as an effective technique for controlling DC motor speed due to its ability to handle system nonlinearities and uncertainties. The proposed system integrates a fuzzy logic controller with a microprocessor, where the microprocessor executes the complex fuzzy logic algorithms. The system utilizes error and change in error signals as inputs to the fuzzy logic controller, which then generates an output signal to the microprocessor. The microprocessor subsequently generates a Pulse Width Modulation (PWM) signal, amplified by a motor driver, to control the DC motor's speed. Feedback from a speed sensor allows for real-time calculation of the error signal. Experimental results from the designed and constructed prototype demonstrate the system's robust performance. For instance, with a constant load of 20 kg, varying the input voltage from 20V to 100V resulted in a stable increase in motor speed from 400 RPM to 510 RPM, showcasing consistent and controllable speed regulation. Similarly, under varying load conditions with an initial input voltage of 5V, the system demonstrated precise control, with speeds ranging from 300 RPM at 2 kg load to 322 RPM at 20 kg load. These results highlight the superior ability of the fuzzy logic-based controller, interfaced with a microprocessor, to provide accurate and stable DC motor speed control across a wider operational range compared to traditional methods, addressing the limitations of noise and uncertainty