Adaptive dynamic sliding mode control for robotic systems via a Fourier estimator

In this paper, using a Fourier estimator, An adaptive dynamic sliding mode controller for robotic systems is developed. In comparison with fuzzy systems and neural networks, a Fourier series is simpler and less computational. The uncertainty includes parametric uncertainty, un-modeled dynamics and external disturbance. These uncertainties are approximated by a Fourier series. Adaptation laws for tuning the Fourier series coefficients are obtained based on the stability analysis. The case study is an articulated robot manipulator driven by permanent magnet DC motors. Simulation results verify the effectiveness of the proposed control approach.

کلیدواژه ها:

adaptive dynamic sliding mode controller ، robotic systems ، Fourier estimator ، uncertainty