Research on Structure Design and Control Method of Underwater Exploration Robot

Abstract

For the sake of complete the detection of complex underwater environment in the engineering construction, this paper designs the structure of the underwater exploration robot according to the actual requirements of the project, and proposes a control method of the underwater exploration robot using neural network to improve the PID control parameters. Firstly, the overall structure and control system layout of underwater exploration robot are designed and planned according to the design requirements. Secondly, aiming at the problems of complex parameter setting and poor real-time performance of system parameters in traditional control methods, the automatic learning characteristics of feedforward neural network and PID controller are combined to realize the online alter of PID control unit parameters. Finally, according to the above method, a PID controller with automatic learning characteristics is designed to control the underwater exploration robot, which can achieve the optimal parameter combination of the underwater exploration robot's motion control, and improve its poor adaptability in underwater motion.