Open AccessResearch on Seeker Servo Platform Based on BP neural network controller
Author(s) -
Wei Tang,
Huhai Jiang,
bin Pu,
Tongtong Zhang,
Rui Mao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/3/032110
Subject(s) - pid controller , artificial neural network , servomechanism , control theory (sociology) , control engineering , matlab , robustness (evolution) , adaptability , servo , computer science , servomotor , servo control , control system , engineering , artificial intelligence , control (management) , temperature control , ecology , biochemistry , chemistry , electrical engineering , biology , gene , operating system
Seeker is the core of precision guided weapon. The performance of its servo mechanism has a decisive impact on the accuracy of guidance weapon. The controller design of seeker servo system is of great significance to improve the function of seeker servo system. The mathematical model of the seeker servo system in the form of transfer function is built. The traditional PID control and BP neural network PID control methods are used to design the controller respectively. Aiming at the limitation of BP neural network, the BP neural network is improved. Finally, the simulation experiment is carried out in Matlab/Simulink. Simulation results show that the neural network PID controller has better performance than the traditional PID controller, so that the system has better adaptability and robustness.