**5. Conclusions**

The mathematical model of the motor and the wheel are used for the traction controller. The angular speed, longitudinal speed, current, and slip are obtained from this model. The current is used in the slave loop, whose objective is to brake the wheel to compensate for the angular longitudinal speed through the motor shaft. The master loop aims to follow an S-curve velocity profile. Three different surfaces were used for the simulations: dry asphalt, wet asphalt, and ice.

A PID controller was implemented to make the comparisons, before the surfaces mentioned above, with the fuzzy controller. The fuzzy controller design followed the same methodology as the one used for the motion controller. This makes the adaptive PID-like fuzzy controller master–slave design methodology easy to reproduce. The PID controller worked well on wet and dry asphalt surfaces, but the controller no longer compensated for speeds when the Quarter-Car robot was presented on an icy surface. The same gains were used for all three trials. The fuzzy controller worked well for all three surfaces, showing robustness to changing surfaces. For future work, a type-2 fuzzy logic controller will be implemented to prove the type reduction algorithms in embedded systems in the slip control applications.
