Research on Trajectory Tracking Control of Underwater Vehicle Manipulator System Based on Model-Free Adaptive Control Method

Abstract

In order to improve the trajectory tracking accuracy of an Underwater Vehicle Manipulator System (UVMS) under uncertain disturbance conditions of ocean current, a Model-free Adaptive Control (MFAC) method was used. Combined with Radial Basis Function Neural Networks (RBFNN), the RBFNN-MFAC method is proposed to improve the performance of the controller. A hydrodynamic model of UVMS was defined in the commercial software, Fluent, to calculate hydrodynamics disturbance, and the mechanism of the dynamic model of UVMS was defined in the commercial software, Adams, to simulate the motion of UVMS. The trajectory tracking performance with various control schemes, including PID (Proportional Integral Derivative), MFAC and RBFNN-MFAC, were analyzed with the Adams and Simulink joint simulation model. The results show that the position tracking accuracy and the speed tracking accuracy with the MFAC control scheme were 68.1% and 81.0% better, respectively, than those with PID control scheme. The position tracking accuracy and the speed tracking accuracy with the RBFNN-MFAC control scheme were 66.3% and 43.1% better, respectively, than those with the MFAC control scheme. The MFAC control scheme and the RBFNN-MFAC control scheme proposed in this paper exhibit good trajectory tracking performance without the precise dynamic model of UVMS, which is of great importance to applications in engineering.