Model Predictive Control Method of AUV Based on Lie Group Theory

Abstract

Model predictive control (MPC) can solve the constraint problems of the unmanned system control. However, the model of autonomous underwater vehicle (AUV) is nonlinear, and the Jacobian matrix changes with the state of the AUV, so the traditional linear MPC method is no longer applicable. This paper presents an MPC motion control method based on Lie group theory. We represented the attitude, velocity and position errors of an AUV as an element in the Lie group, and linearized the MPC model by combining the dynamic model of the AUV, so that the Jacobian matrix is only related to the expected value, and the control performance is improved. Simulation results show that, compared with the traditional MPC algorithm, the algorithm in this paper shows stronger robustness when the AUV suffers from large disturbance and state expectation mutation.