A USDE-Based Control for Bilateral Teleoperation Systems With Time-Varying Delays

In this paper, a simple but effective control scheme is proposed for bilateral teleoperation systems with variable communication time-delays. The robotic models are first reformulated and an unknown system dynamics estimator (USDE) is constructed to estimate the lumped uncertainties without using the accelerations, where only low-pass filtering operations and trivial algebraic calculations are used. The USDE is then incorporated into the controller design to compensate for the effects of uncertainties. The stability of the closed-loop system is rigorously proven via the Lyapunov theorem for all three motion states: free motion, tracking motion, and contact motion. The salient feature over traditional control strategies is that apart from position and velocity synchronization, compliance can be guaranteed in the tracking motion and force transparency can be obtained in the contact motion. Moreover, the proposed USDE and control have simple structures and less parameters, which facilitate their practical application. Both simulation and experimental results are presented to demonstrate the effectiveness of the proposed methods.
Note to Practitioners
—Bilateral teleoperation systems are widely used in nuclear science, space research, telesurgery, microassembly and other fields, where human or unmanned robotics cannot perform certain tasks. However, in the teleoperation, several factors such as external forces and communication delays between local and remote robotics will affect the control performance, e.g., synchronization, compliance and transparency. This paper proposes a USDE-based control method that can handle unknown system dynamics and variable time-delays without using the acceleration signals, while the system’s stability in all the three motion states: free motion, tracking motion and contact motion can be retained, and the corresponding position and velocity synchronization objectives can be achieved. This method has the certain advantages including simpler structures, less tuning parameters and better control performances, facilitating its practical applications. Finally, both simulation and experiments are illustrated to verify the theoretical claims.