A Time Delay Estimation Based Adaptive Sliding Mode Strategy for Hybrid Impedance Control

This paper is inspired by the automation of cleaning tasks required inside the endogenous environment. This work intends to develop a robust adaptive strategy for force-position control, using robotic manipulators. With this objective, the operational/task space is decoupled into two sub-spaces, and the impedance model for the manipulator is designed using the standard second-order filters. The impedance filter generates the reference commands for the inner loop, which assures bounded position and force tracking. A delay estimation based adaptive sliding mode strategy is proposed for carrying out the tracking objective, and its convergence is proved using the Lyapunov-Razumikhin theorem. The controller uses past data to estimate the uncertainties in the error dynamics and exploits the sliding mode strategy to provide robustness in the closed-loop. This technique circumvents the under/overestimation issues, and linear/nonlinear parametrization requirements in conventional adaptive schemes. Multiple numerical simulations and experiments are performed, and the results point to the validity of the proposed control law in real-world settings.