Controle de velocidade de um robô móvel autônomo utilizando lógica fuzzy

Abstract

The increasing adoption of autonomous mobile robots in industrial, logistics, and academic applications imposes significant challenges on speed control, especially in scenarios subject to nonlinearities, uncertainties, and load variations. Traditionally, speed control is performed using classical controllers, such as the Proportional–Integral (PI) controller, which provides satisfactory performance in linear systems but exhibits limitations under dynamic operating conditions. In this context, this work proposes the development and validation of a fuzzy logic–based speed control system applied to a differential-drive autonomous mobile robot. The fuzzy controller was designed using a Mamdani-type inference system, with the speed error and the variation of the error as input variables and an incremental control output. The methodology included experimental plant characterization, embedded system implementation, and experimental tests under different load conditions. The performance of the fuzzy controller was compared with that of a classical PI controller using metrics such as response time, steady-state error, and the Integral of Absolute Error (IAE). Experimental results demonstrate that the fuzzy controller achieved improved robustness and superior speed tracking performance, particularly under load variations, validating the proposed hypothesis and highlighting the potential of fuzzy logic for mobile robotics applications.