Comparison Between Fuzzy and Non-fuzzy Ordinary If–Then Rule-Based Control for the Trajectory Tracking of a Differential Drive Robot

The paper proposes fuzzy and non-fuzzy controllers as two control techniques for trajectory tracking of a differential drive mobile robot. The first approach relies on fuzzy logic. Fuzzy logic systems represent knowledge via fuzzy rules. The large number of possible rules complicates the controller and has an impact on timing decision. Logic methods like Karnaugh maps and Quine McCluskey's algorithm have been offered as ways to adapt and reduce the amount of fuzzy rules. An approach based on Karnaugh maps to reduce the number of fuzzy rules without binary coding has been proposed. The second technique, on the other hand, is a non-fuzzy approach that employs the same rules as the reduced fuzzy controller, namely, non-fuzzy (ordinary) If–then rules. Simulation tests and a comparison of fuzzy and non-fuzzy controllers were used to test the efficiency of the proposed controllers.