Two-wheeled self-balancing robots (TWSBRs) are difficult to control because they are nonlinear, unstable, and underactuated, particularly when balance, velocity regulation, and line tracking must be achieved simultaneously. This paper proposes a hybrid parallel control architecture for a line-following TWSBR operating on straight segments, 90∘ curves, and a 15∘ slope. Balance stabilization is handled by a classical PD loop, while traslational velocity is regulated by an adaptive fuzzy PI controller, and line following is performed with an adaptive fuzzy PD controller. The fuzzy modules adjust the effective gains based on tracking errors, thereby improving robustness to disturbances, sensor noise, and changes in operating conditions. The complete strategy is implemented on a low-cost PIC18F4550 microcontroller. Experiments show that the fuzzy line-following controller reduces the orientation tracking error compared with a conventional controller. At 0.10ms, RMSE decreases from 0.042rad to 0.038rad, and at 0.175ms, it decreases from 0.083rad to 0.066rad. The fuzzy approach also improves IAE (1.317rads to 1.185rads) and ISE (0.242rad2s to 0.153rad2s) at 0.175ms, while maintaining similar maximum error (0.299rad to 0.261rad). Overall, the proposed hybrid scheme achieves better adaptability without retuning. These results support real-time deployment on resource-limited platforms.
Rojas-Galván et al. (Fri,) studied this question.