Research on Servo System of Unmanned Amphibious Rescue Vehicle for Sudden Flood Based on Intelligent Algorithms

At present, there are some problems in controlling the servo system of Unmanned Amphibious Rescue Vehicle (UARV) with PID controller, such as low track tracking accuracy, poor control error, poor stability and safety performance. A servo control system of UARV based on BP neural network tuning PID controller is proposed and designed. The driving model of servo control system of UARV in sudden flood disaster is established. This model is used as the controlled object. BP neural network is used to learn the performance of servo control system of UARV. BP neural network is used to tune the PID controller. Gradient descent method is used to modify the weighting coefficient of the controller to realize the adaptive adjustment of the controller and control the UARV in sudden flood disasters. The experimental results show that the servo system of UARV based on BP neural network tuning PID controller effectively improves the trajectory tracking accuracy, has better flexibility, the vehicle runs smoothly, and the rescue personnel are safe because of unmanned driving.