Intelligent Controller Design for a Blowdown Supersonic Wind Tunnel

Abstract

In this paper, first, the nonlinear mathematical model of special Blowdown Supersonic Wind Tunnel (BSWT) consisting of a set of ordinary differential and algebraic equations is 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 the stagnation pressure and the 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 BSWT with the aim of achieving the accurate and acceptable desired results. Performance of the BSWT using optimized fuzzy controller by ANN is found to be satisfactory, as confirmed by the results.