Adaptive Force/Position LQR Control of Asymmetric Teleoperation System Based on Kalman Filtering

Metallurgical industrial robots are increasingly relied upon in modern industries, with growing demands for higher performance. Teleoperation systems, which consist of a master robot and a slave robot, are widely used in the metallurgical field. Stability, tracking, and transparency are key performance requirements for these systems. This study proposes an asymmetric teleoperation system with a novel 6-degree-of-freedom (6-DOF) haptic device as the master robot and a Baxter robot as the slave robot. To enhance the system's tracking and transparency, an LQR (Linear Quadratic Regulator) control algorithm combined with Kalman filtering is introduced for force/position control. Simulation and experimental results demonstrate that the LQR + Kalman filter control algorithm significantly improves control performance compared to the previous Adaptive Fuzzy & PID control algorithm. The system exhibits reduced trajectory tracking errors and enhanced force feedback accuracy, meeting the stringent requirements of asymmetric teleoperation systems in the metallurgical industry. The proposed control strategy not only optimizes the performance of the teleoperation system but also provides a robust solution for real-time control applications in complex industrial environments.