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Research On Thrust Control Of Variable Flow Solid Ducted Rocket

Posted on:2019-10-17Degree:MasterType:Thesis
Country:ChinaCandidate:Y C ZhouFull Text:PDF
GTID:2392330611993526Subject:Aeronautical and Astronautical Science and Technology
Abstract/Summary:PDF Full Text Request
To satisfy the need of supersonic cruising of the missile,this paper did lots of studies about flow and thrust regulation control of flow variable solid ducted rocket,by the method of theoretical analysis,simulation,and experiments.First of all,this paper do the research on the model of flow variable solid ducted rocket,which uses a baffle valve gas regulation device.This paper identifies model of the baffle valve and brushless DC servo motor in the device.Stable and dynamical models of the thrust system with variable gas was built,including flow rate of gas generator which is a non-minimum phase system.Designs schemes and procedures of thrust regulation control.In the outer control,model rebuilding was needed to solve the problem of data store and quick calculating.Based on BP neural network,models of height,Mach number,AoA,AoS,flow of gas and thrust was built.The models of gas generator were verified and amended by experiments.Compared with thrust database model,the BP neural network model is only 10 KB and 3000 times faster.In the inner control,gas generator is a nonlinear and variable parameter system.To reduce overshoot,undershoot,and settling time,a self-adaptive RBF neural network control algorithm was used tentatively.Mathematical simulations were proceed to test the algorithm preliminary.Thrust regulation control simulations and experiments were executed.Including mathematical simulation based on MATLAB and SIMULINK,hardware-in-the-loop simulations which have controller and brushless DC servo motor in kind.The simulations prove that the control system of thrust regulation can achieve the goal of control variable flow solid ducted rocket thrust.
Keywords/Search Tags:flow variable, thrust regulation control, models of ducted rocket, models building based on BP neural network, self-adaptation RBF neural network control
PDF Full Text Request
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