Advanced Flow Control for Supersonic Blowdown Wind Tunnel Using Extended Kalman Filter

Author:

Xi Jiaqi1,Li Mian2,Zhang Qiang13,Wang Zhaoguang1

Affiliation:

1. University of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China

2. University of Michigan—Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China e-mail:

3. Department of Mechanical Engineering and Aeronautics School of Engineering and Mathematical Sciences, City University London, Northampton Square EC1V 0HB, London

Abstract

Supersonic blowdown wind tunnels provide controlled test environments for aerodynamic research on scaled models. During the experiments, the stagnation pressure in the test section is required to remain constant. Due to nonlinearity and distributed characteristics of the controlled system, a robust controller with effective flow control algorithms is required for this type of wind tunnels. In this paper, an extended Kalman filter (EKF) based flow control strategy is proposed and implemented. The control strategy is designed based on state estimation of the blowdown process under the EKF structure. One of the distinctive advantages of the proposed approach is its adaptability to a wide range of operating conditions for blowdown wind tunnels. Furthermore, it provides a systematic approach to tune the control parameters to ensure the stability of the controlled air flow. Experiments with different initial conditions and control targets have been conducted to test the applicability and performance of the designed controller. The results demonstrate that the controller and its strategies can effectively control the stagnation pressure in the test section and maintain the target pressure during the stable stage of the blowdown process.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference12 articles.

1. Supersonic, Variable-Throat, Blow-Down Wind Tunnel Control Using Genetic Algorithms, Neural Networks, and Gain Scheduled PID;Appl. Intell.,2008

2. Nelson, D., 1989, “Wind Tunnel Computer Control System and Instrumentation,” Proceedings of the 35th International Instrumentation Symposium, Instrument Society of America, Orlando, FL, May 12, pp. 87–101.

3. A Practical Design for a Multivariable Proportional-Integral Controller in Industrial Applications;Ind. Eng. Chem. Res.,1997

4. Eric, B., Frank, L., Philip, P., Richard, M., Donald, W., and Dutton, J., “Supersonic Blowdown Wind Tunnel Control Using LABVIEW,” Proceedings of the 46th AIAA Aerospace Sciences Meeting and Exhibit, American Institute of Aeronautics and Astronautics, Reno, NV, January 5–8.

5. Scott, R. C., “Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks,” Proceedings of the SPIE's 7th Annual International Symposium on Smart Structures and Materials, International Society for Optics and Photonics, Newport, CA, March 1–5, pp. 232–243.

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