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Considering the external disturbances and dynamic uncertainties during the process of the trajectory tracking, this paper aims to address the problem of the welding robot trajectory tracking with guaranteed accuracy.

The controller consists sliding mode control, fuzzy control and low pass filter. The controller adopts low-pass filter to reduce the high frequency chattering control signal in sliding mode control. The fuzzy control model is used to simulate the external disturbance signal and the dynamic uncertainty signal, so that the controller can effectively restrain the chattering caused by the sliding mode control algorithm, realizing the track of the welding robot effectively and improving the robustness of the robot.

An innovative experiment device was adopted to realize the performance of the proposed controller. Considering the kinematic and dynamic uncertainty during the process of robot tracking, the tracking accuracy was realized within 0.3 mm.

This paper uses Lyapunov stability theory and Barbalat theorem to analyze the stability of the proposed controller.

This paper aims to address the collision problem between robot and the external environment (including human) in an unstructured situation. A new collision detection and torque optimization control method is proposed.

Firstly, when the collision appears, a second-order Taylor observer is proposed to estimate the residual value. Secondly, the band-pass filter is used to reduce the high-frequency torque modeling dynamic uncertainty. With the estimate information and the torque value, a variable impedance control approach is then synthesized to guarantee that the collision is avoided or the collision will be terminated with different contact models and positions. However, in terms of adaptive linear force error, the variation of the thickness of the boundary layer is controlled by the new proximity function.

Finally, the experimental results show the better performance of the proposed control method, realizing the force control during the collision process.

Origin approach and origin experiment.