Research of Financial Robot Control System Based on Hopfield Neural Network

Abstract

In order to improve the intelligence level of financial management, a financial service robot based on Hopfield neural network is proposed. The manipulator is one of the important components of the robot system, and the trajectory tracking control of the manipulator is the key problem for the robot to perform the follow-up work. Due to the influence of uncertain factors such as external interference, the trajectory tracking control of manipulator has poor stability, low accuracy and long time. Therefore, an improved HOPFIELD neural network trajectory tracking control method for manipulator is proposed. Using Lagrange function, this design defines the dynamic equation of manipulator system and establishes the dynamic model of manipulator. Using the term function of Newton algorithm, the system trains HOPFIELD neural network and realizes the trajectory tracking control of the manipulator. Combined with the principle of robot kinematics, HOPFIELD neural network is used to control the robot arm. Finally, the above scheme is verified by simulation. The results show that the financial service robot designed in this study can run normally, and the robot can realize the planning and control of the manipulator through the controller.