Mohammad Reza Shokoohinia - Department of Electrical and Robotic Engineering Shahrood University of Technology Shahrood, Iran,
Mohammad Mehdi Fateh - Department of Electrical and Robotic Engineering Shahrood University of Technology Shahrood, Iran,
Reza Gholipour - Department of Electrical and Robotic Engineering Shahrood University of Technology Shahrood, Iran,

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.

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