Underwater Maneuvering Target Tracking Control Based on Model Predictive Control

Abstract

AbstractAiming at the problem of underwater maneuvering target tracking, this paper studies the tracking control method of the underwater unmanned vehicle based on model predictive control (MPC). First, an interacting multiple model extended Kalman filter (IMM-EKF) is constructed to predict the trajectory information of dynamic targets. The interactive multiple model Kalman filter comparison shows the accuracy of the IMM-EKF for predicting the maneuvering target. Then, the underwater tracking control of maneuvering target is realized by using MPC, which solves the problem of speed variable beyond the limit in linear quadratic regulator (LQR) algorithm, and makes the tracking result more stable and reliable. Simulation results show that the proposed target tracking control method is effective and feasible.KeywordsTarget tracking controlInteractive multiple modelExtended Kalman filteringModel predictive controlUnmanned underwater vehicle