Fuzzy Neural Network Control Of A Weapon System

This paper is aimed to improve the control performance of an artillery servo system which requires high control qualities such as the speediness, accuracy and stability under hard circumstances like the huge inertia, the great variation of the load and the great impulsion.The main contents of this paper include three parts: the hardware design of the servo system , the software programming of the system and the whole system's debugging. The part of the hardware emphasizes on the design of the servo amplifier and the testing of the circuit. the software use a neural net to identify the servo system. Learn the parameter of the neural net out of system to get the basic parameter. When the error is bigger than certain value , it should be controlled by time-best choiceness and system is permitted to move at the greatest velocity. Because of the hard circumstance that the system works on, the part of the software emphasizes on attempting and exploring the combining of the fuzzy control with neural net, then bring forward a new controller which is named as fuzzy-neural net controller which learn the parameter as the system work. The measure above can resolve the contradiction of control precision and the response real time very well.According to the results of the simulation and real experiments, it is known that with the controller which is based on fuzzy and neural net the system can satisfy all targets and performance even under the hard circumstances.