Research on kinematics and fractional order active disturbance rejection control of skating training robot

Abstract

Abstract. Speed skating training imposes rigorous requirements on movement accuracy and dynamic stability. Traditional training relies heavily on coaches' subjective experience; exoskeleton robots suffer from limitations of large additional inertia and insufficient flexibility. Although cable-driven robots possess the advantage of flexible transmission, existing control methods fail to meet the demand for high-precision trajectory tracking. To address this issue, this study conducted systematic research: a cable-driven robotic mechanism adapted for skating training was designed, and a geometric model of fixed-mobile coordinate systems was established, with the Newton–Raphson iterative method employed to solve forward and inverse kinematic equations. An improved fractional-order active disturbance rejection control (FOADRC) strategy was proposed, which removes the tracking differentiator of traditional ADRC and integrates a fractional-order extended state observer (FOESO) with a fractional-order PD control law, thereby enhancing dynamic response and anti-disturbance capability. Human skating movement data were collected using the NOKOV infrared motion capture system, and reference trajectories were generated via fitting with eighth-order Fourier series. Comparative simulations with traditional PID control were performed. The results demonstrate that the motor angle tracking error under the FOADRC strategy is significantly reduced, with improved control precision. This study provides a practical solution for precise skating training and offers reference value for the development of intelligent auxiliary equipment in competitive sports.