Research On Temperature Multivariable Coupling Control Of Missile Tail Flame Simulator

The Missile plume simulator is a kind of infrared target simulator applied to air defense training.In the infrared target simulator,the temperature of the heating rod of the infrared probe directly affects the infrared radiation intensity,and the stability of its temperature control directly affects the actual use effect of the whole target simulator.The temperature of infrared emitter is a complex control object,and it is coupled with many temperature variables.There is an urgent need for a decoupling control to control the temperature of the target simulator in a stable range.In order to solve this problem,this paper first analyzes the main principles of the design and application of the missile plume simulator,including the infrared radiation principle involved in the hardware design and the overview of the neural network principle used in the temperature coupling control.According to the coupling control principle,the coupling analysis of the system is carried out,and the traditional method and neural network method are used to decouple the simulation of the system,and the effects of several decoupling methods are compared.Then,the hardware part of the tail flame simulator is designed and researched.According to the analysis of the temperature characteristics of the hardware system,the temperature coupling system of the tail flame simulator is modeled,and the neural network PID Decoupling Control System Based on the inverse system is designed.In order to prove the reversibility of the system,the system model is established.In order to select the appropriate network structure,the neural networks with different structures are simulated and analyzed.Finally,RBF neural network algorithm is used.RBF is used to approach the inverse system,Matlab is used to simulate and analyze the training effect under different network structures,and the most appropriate network structure is selected.Then,the inverse system and the original system are combined to form a pseudo linear system,so that the coupling system can be linearized and decoupled.The simulation results show that the decoupling effect is obvious,and the system has better anti-interference ability.For the decoupled subsystem,the incremental PID method is used to control,so as to further improve the stability of the composite system.The simulation results show that the inverse system decoupled control method based on RBF neural network can decouple the multivariable temperature of the missile plume simulator system,and the decoupled system has a certain anti-interference ability.