Adaptive MPC trajectory tracking for AUV based on Laguerre function. (1st October 2022) - Wang, Weiran; Yan, Jinghao; Wang, Hui; Ge, Huilin; Zhu, Zhiyu; Yang, Guanjun
Abstract: When the autonomous underwater vehicle (AUV) traces the trajectory under complex hydrological conditions, the real-time performance of system is slow and the accuracy of tracking is poor. To solve this problem, an adaptive predictive control method based on Laguerre function is designed in this paper. This method contains two parts: one is the adaptive MPC module which is used to track the trajectory accurately; the other is the Laguerre function module which is applied to reduce computations significantly. In the adaptive MPC module, the recursive least squares algorithm is introduced to identify the model parameters of the system to improve the accuracy and the robustness. However, this method may cause a great increase in computation when AUV works in the complex environment. Therefore, in Laguerre function, one reconstruction of the controller input variables is introduced to reduce the matrix order of the objective function. The simulation results show that the designed method has a good performance in the respects of the dynamic, the anti-interference and the robustness when AUV tracks the trajectory with the less amount of calculation. Highlights: It proposed a five-degree-of-freedom linear model for AUV. And the adaptive MPC strategy is established based on this model. It solves the problem of parameter adaptation in traditional MPC and the problem of the error in linearization process. The internal matrix of controller is reconstructed with Laguerre function to improve the response speed of the controller.