Adaptive Hybrid Position/Force Control for Robot Based on Time Delay Control

This paper proposes an adaptive hybrid position/force control algorithm based on time delay control. The purpose is to improve the accuracy of position and force in uncertain environments. In position control subsystem, time delay control which does not depend on the system model is employed to cancel all the nonlinear terms in the robotic system. An adaptive gain is introduced to reduce the time delay estimation error in uncertain environments. In force control subsystem, the unknown environmental parameters were identified online by the recursive least squares algorithm, and the contact force between the end-effector and environments was obtained. The stability of the system is analyzed via Lyapunov function, and the effectiveness of the proposed control algorithm is verified by simulations. The proposed control algorithm is adaptable to uncertain environments and can ensure the accuracy of simultaneous position and force tracking of the end-effector. The position error is about 0.016 m and the force error is about 0.034 N.