Abstract
Abstract To cope with the complex external environment of the robot, an online adaptive control method for industrial robots is implemented by using robot dynamic parameters as control variables. A Newton-Euler method is implemented to establish a rigid body dynamics model for the robot. Subsequently, we confirm the possibility of dynamic parameter adaptive control by employing the Lyapunov stability theory and derive the dynamic parameter estimation law. Three methods are proposed to realize the observation matrix containing reference information in the adaptive control algorithm. Through physical experiments, it is verified that the dynamic parameter adaptive control is superior to traditional PPI control, and its position tracking error and anti-interference ability are significantly improved.
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