Hybrid force/position control of a collaborative parallel robot using adaptive neural network

Abstract

In this paper, a new stable adaptive neural network control scheme has been presented for hybrid position and force control of the Delta parallel robot. Force control is an important technique in programming and safety for collaborative robots. The hybrid control scheme is introduced to tackle the interaction problem between the robot and its environment such that the robot follows the position trajectory and desired force, which is applied in a certain position. The goal of the control is applying desired force trajectory in a certain position in which there is a constraint for movement. Fewer parameter settings, adaptive algorithm, and efficient control input signals are the advantages of the proposed controller.