A deepening controlling method of an underactuated automatic
underwater vehicle based on a neural network
back stepping method relates to the technical field of control of the underactuated automatic
underwater vehicle. The deepening controlling method includes first collecting pressure information through a
pressure sensor, obtaining corresponding depth of the automatic
underwater vehicle (AUV) by calculation according to the pressure information, then building a
mathematical model of the underactuated automatic
underwater vehicle and a robust deepening controller model, building a
mathematical model of the underactuated AUV according to
ocean current environment and AUV water
power parameter, designing the robust deepening controller model by adopting the feedback gained
back stepping method, finally obtaining
online learning arithmetic based on neural network weight and self-adaptive law of self-adaptive robust controller parameter, conducting online recognition and error
estimation on uncertainty existing in the obtained
mathematical model, compensating and optimizing final output signals of the controller, and achieving deepening control of the underactuated AUV by adopting the controller.