Abstract
This paper presents a methodology for the control of robot manipulators which combines parametric adaptive control with Artificial Neural Network (ANN) compensation of dynamic uncertainties like friction. The proposed method utilizes passivity based parametric adaptive control approach and makes use of the ANN models as generic identifiers to compensate for unmodelled friction effects. The parameter update equations for the parametric adaptive model and the ANN model are driven by both tracking error and the prediction error. The methodology is tested for the control of Direct Drive SCARA arm and performance is compared with standard adaptive control schemes.
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