Hybrid force/position approach for flexible-joint robot with fuzzy-super twisting sliding mode control

Abstract

This paper presents a novel hybrid force/position control strategy for rigid-link flexible-joint robots (RLFJR) operating in constrained environments. The proposed approach integrates fuzzy logic with the super-twisting sliding mode control (FSTSMC) algorithm to enhance robustness and reduce the chattering phenomenon typically associated with sliding mode controllers. A two-loop control structure is adopted: an inner loop dedicated to position control using the FSTSMC, and an outer loop for force regulation employing a classical PI controller. To address the challenge of limited joint state measurements in industrial robots, a high-gain nonlinear observer is designed for accurate joint state estimation. The effectiveness of the proposed method is validated through simulations on a PUMA 560 robot model, performing a circular trajectory while applying a constant contact force. Results demonstrate high tracking precision in both joint and Cartesian spaces, rapid convergence of errors, and significant mitigation of chattering effects, confirming the feasibility and efficiency of the proposed control scheme for interaction tasks involving flexible-joint manipulators.