Adaptive Robust Control Schemes for an Uncertain 2-dof Manipulator Subjected to Disturbances
DOI:
https://doi.org/10.31181/jidmgc11202520Keywords:
Adaptive control, Robotic manipulator, Neural networksAbstract
This paper focuses on the tracking problem for a 2-link rigid robotic manipulator with model uncertainties and disturbances. The manipulator is always subject to disturbances such as environmental disturbance, measurement noise, and so forth, which makes the controller design a far more complex task. By combining the ``core function" with a neural network, the deep-rooted information of the system uncertainties can be extracted and then further compensated by a robust method. In addition, in this paper, the disturbance is formulated as a norm-bounded variable, and thus the adaptive robust controllers based on backstepping design and filtered variables are developed simultaneously. Finally, simulation studies show the effectiveness of the control algorithms.
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