Simulation Research on the Depth Control of Remote Operated Vehicle Based on Single Neuron Pid
Download as PDF
Zexin Jiang, Shaohan Chen
For the depth control of ROV (remote operated vehicle), this paper established the function model of ROV motion process transfer according to the dynamics theory, and used PID control algorithm to control the depth. Considering the large disturbance in the process of depth keeping, the difficulty of getting accurate ROV model parameters, as well as the poor robustness and dynamic performance of traditional PID control, the neural PID controller is adopted. The simulation results show that the single neuron PID controller greatly improves the dynamic performance of the depth control. When the model parameters change slightly, it has better anti-interference performance and robustness.
Remote operated vehicle, Depth control, Single neuron pid, Robustness, Simulink simulation