Abstract
This paper focuses on the fault tolerant control of autonomous underwater vehicles (AUVs) in the presence of dynamic uncertainties and potential thruster failure issues. For this, an adaptive proportional-integral sliding mode-based fault tolerant control (APISM-FTC) is proposed to drive the AUV to follow the desired trajectory, in the event of unknown thrusters failure and thrusters saturation. Radial basis function neural network (RBFNN) and an adaptive approach are used to evaluate the dynamics uncertainty during the construction of the APISM-FTC controller. To guarantee that all tracking errors asymptotically converge to zero, a comprehensive theoretical analysis and mathematical proof based on Lyapunov stability analysis are implemented. The simulation experiments on two fault conditions are carried out, respectively, and the control effects under normal conditions are compared. It can be shown that the designed APISM-FTC method can make the system reach a stable state quickly, and can still have a good control performance in the case of the failure of the thruster.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
