A comparison of adaptive trajectory tracking controllers for wheeled mobile robots

Two adaptive trajectory tracking controllers for wheeled mobile robots are tested in this work. Adaptively tuned proportional control is one approach, where as the other controller uses a Universal Adaptive Stabilization (UAS) based technique. Using simulations, the robustness of the above controllers is quantified in the presence of measurement noise. The robustness is measured in terms of the Integral of absolute magnitude of the error (IAE), the Integral of square of the error (ISE), and the Integral of time multiplied by the absolute value of the error (ITAE) criteria. It is observed that the UAS based technique shows fast convergence in the absence of noise. To combat the effect of noise, the authors reset the adaptation gains after the adaptation gains reach a preset bound. With this technique it is found that the UAS based technique converges to the trajectory being tracked faster than the adaptively tuned proportional controller, and also faster than a traditional inputoutput state feedback linearization based controller.