Research On Trajectory Planning Of Throat Block And Flexible Plate In Semi-flexible Wall Nozzle

Wind tunnel experiment is a significant part in the development of modern fighter aircrafts and the nozzle is an important part of the wind tunnel.This paper takes the continuous transonic semi-flexible wall nozzle as the research background and mainly studies the throat block and the flexible plate in the semi-flexible wall nozzle,the rigid-flexible coupling cooperative control of which performs the forming motion of the shaped surface.In the case of the known initial state and final state,the path planning is performed to minimize the stress generated on the flexible plate.The whole set of nozzles uses the hydraulic system as the power source for each drive unit.The hydraulic system uses double-acting asymmetric cylinders with proportional servo valves as the control core.The control system is baed on iterative learning PID.The main contents of this article are as follows.Firstly,this paper gives the overall explanation of the mechanical structure of the throat block,the flexible section and their overlap.The rigid-flexible coupling simulation is performed by ADAMS and PATRAN/NASTRAN to provide rigid-flexible coupled data which is used by a back-propagation neural network to establish a rigid-flexible coupled model of the throat block and the flexible plate of the semi-flexible nozzle.Secondly,the differential evolution algorithm is used to solve the preliminary optimal trajectory.Based on the rigid-flexible coupling model of the throat block and the flexible plate of the semi-flexible nozzle,the interpolation points are optimized and the evaluation function is constructed which are used in a differential evolution algorithm.The obtained interpolation points are fitted using a cubic spline curve to obtain an optimal trajectory.Afterwards,the hydraulic control system is designed.The hydraulic system of the throat block and the flexible plate of the semi-flexible wall nozzle is introduced.The hydraulic system equipment is designed and calculated,including the maximum working pressure,maximum flow,tank volume and accumulator.Also key components are selected,including pumps,motors,hydraulic valves,hydraulic cylinders and displacement sensors.The transfer function is established for the double-acting asymmetric cylinder based on proportional servo valve,due to which a PID controller based on the Iterative learning is used.The obtained optimal trajectory is used as the input quantity to simulate.Lastly,the particle swarm algorithm is used to obtain the optimal trajectory of the whole system.The optimization object,evaluation function and fitting method are the same as the differential evolution algorithm.The preliminary optimization result of Chapter 3 is taken as the initial value.The established hydraulic control system is considered into the optimization process.The group algorithm is optimized to obtain the optimal trajectory of the whole system.