Research On Model Predictive Control For AUV Based On ROS

Autonomous Underwater Vehicle(AUV)is an important technical means of sustainable development and utilization of Marine resources.In recent years,AUV has developed rapidly and is becoming an important platform for scientific research,military industry and other fields to collect and observe Marine environmental characteristic data.However,the problem of AUV motion control is relatively complex,such as the establishment of accurate AUV motion model,improve the performance of the controller and other key problems need to be considered and solved at the same time.This paper mainly carries out the following research work:On the basis of the Model Predictive Control(MPC)algorithm,the kinematics and dynamics equations of the AUV are established,and the over-actuated AUV Model is deduced.In traditional model predictive control method of quickness and achieve balance of anti-interference,combining with the study of AUV motion characteristics,calculating method of cost function of the MPC controller based on the worst-case is improved,and with the method of linear matrix inequality constraints for the processing,optimizes the prediction time domain method,selecting improved optimality of model predictive control method.On this basis,the path tracking based on model predictive controller is studied.This study to Robot Operating System(ROS)to establish the simulation platform,to improve the performance of model predictive controller and the realization of the path tracking has carried on the simulation,some parameters on the stability of the improved model predictive controller,the control performance and the effect of parameter sensitivity,shows that the improved model predictive control method for suitability and effectiveness of the AUV motion control...