Overhead Weapon Gun Control System Robust Control Research

The performance of the gun control system of overhead weapon is a bottleneck, which restrict the firing accuracy and reaction rates of artillery.In order to develop the new overhead weapon, the study of the gun control system becomes important. Based on the development of a new overhead weapon present work mainly focuses on its identification and control strategy of the gun control system.Firstly, the semi-physical simulation test bench is structured based on hardware of the loading and testing device,as the object of researching.The graph of speed response is got after input some voltage to the semi-physical simulation test bench.Then calculate model of the system based on the graph of speed response,in order to design the controller.Then,on the basis of the semi-physical simulation test bench, the input-output data of the system is proposed as the data of system identification. The back-propagation neural network (BP) is used for system identification in this paper.In order to overcome defects of BP, so another method which based on genetic algorithm (GA) is also proposed. The experiment results prove the validity of this method.Finally, H∞mixed sensitivity controller is applied in the gun control system. The sensitivity function is proposed for calculating the controller. The results show that controller has excellent effects in controlling typical input, and can fulfill the capability of the system.