Research on trajectory tracking method of spherical robot based on MPC

DOI:	10.11809/bqzbgcxb2024.07.039
Keywords:	spherical robot; nonlinear dynamic model; model predictive control; rolling optimization; trajectory tracking
Abstract:	The trajectory tracking control of a spherical robot driven by a pendulum suffers from underactuation and nonlinearity, making it difficult to accurately follow desired trajectories. To address this, a Model Predictive Control (MPC) based trajectory tracking control method is proposed. This method utilizes the Lagrangian dynamics model and reference motion trajectory to derive a predictive model for the state deviation of the spherical robot, incorporating Taylor linearization and temporal discretization. Subsequently, with the objective of minimizing trajectory tracking errors within a future time horizon, subject to constraints on control inputs and control increment, a quadratic programming problem is formulated to optimize the rolling torques of the long and short axis motors of the spherical robot. The optimization results are used for torque control of the motors at specific control steps, enabling the robot to track the desired reference trajectory. Simulation results demonstrate that compared to the traditional PID control method, the proposed MPC method reduces the maximum lateral tracking error by 0.664 4 m and the maximum longitudinal tracking error by 0.112 1 m. The tracking error curve remains close to zero, indicating significant advantages in terms of trajectory tracking accuracy and stability.
Issue:	Vol. 45 No. 7 (2024)
Published:	2024-07-26
PDF HTML