Abstract

Blowdown supersonic wind tunnel (BSWT) is a ground based facility to simulate flight conditions of space vehicles in the supersonic flow regime. BSWTs are generally operated with a constant stagnation pressure in the settling chamber, and constant Reynolds number in the test section, with control usually provided by one or more control valves. In this paper, first, the nonlinear mathematical model of the special SWT consisting of a set of ordinary differential and algebraic equation was developed in Matlab/Simulink software environment. At the second step, an Artificial Neural Network (ANN) is used for finding the optimum membership functions of the Fuzzy Logic Controller (FLC) system. This method can help for reasonable system recognition. In this step, by designing and training a feed-forward multilayer perceptron neural network according to the available database which is generated from mathematical model; a number of different reasonable functions for valve opening angle (VOA) in various test conditions are determined. These functions are used to define the desired VOA fuzzy membership functions (MFs). Next, a Proportional-Derivative FLC (PD-FLC) system is developed in the Simulink toolbox to control a relationship between stagnation pressure and temperature in the plenum chamber, which presents the Reynolds number in the test section. A synthetic algorithm combined from FLC and ANN is used to design a controller for a blowdown SWT with the aim of achieving the accurate and acceptable desired results. Performance of the blowdown SWT using optimized fuzzy controller by ANN is found to be satisfactory, as confirmed by the results.

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