Designing similarity measurement with distance measure and application on laterally directional mode flight test

Abstract

Similarity measure construction has been proposed as fault detection of flight test method in order to obtain the primary control surface stuck and the combination stuck of primary control. Similarity measures were obtained through analyzing the certainty and uncertainty of fuzzy membership functions, which were designed based on well-known Hamming distance. It was applied to the fault detection of primary control surface stuck of uninhabited aerial vehicle (UAV). At post-failure control surface, if the UAV is controllable and trimmable using other control surfaces, the UAV is able to fly or return to the safety region through reconfiguration of flight control system. To detect the fault, similarity measure computations were carried out. This result could be applicable with the real-time parameter estimation method. By monitoring the value of coefficients due to the control surface deviation, it becomes aware that the control surface fault occurs or not. The control surface stuck position and value were separated by comparing the trim value with the reference value. This is the advantage of increasing in reliability without adding sensors or with additional low cost.

Keywords

similarity measure / fault detection and isolation / real-time parameter estimation / control surface stuck

References

[1] LeeS. H., ParkH. J., ParkW. J.. Similarity computation between fuzzy set and crisp set with similarity measure based on distance [J]. Lecture Notes in Computer Science, 2008, 4993: 644-649

[2] FanJ. L., XieW. X.. Distance measure and induced fuzzy entropy [J]. Fuzzy Set and Systems, 1999, 104(2): 305-314

[3] LeeS. H., KimY. Y., CheonS. P., KimS. S.. Reliable data selection with fuzzy entropy [J]. Lecture Notes in Computer Science, 2005, 3613: 203-212

[4] LiuX.. Entropy, distance measure and similarity measure of fuzzy sets and their relations [J]. Fuzzy Sets and Systems, 1992, 52(3): 305-318

[5] FanJ. L., XieW. X.. Distance measure and induced fuzzy entropy [J]. Fuzzy Set and Systems, 1999, 104: 305-314

[6] ParkW. J., LeeS. H., SongJ. I.. Fault detection and isolation of DURUMI-II using similarity measure [J]. Journal of Mechanical Science and Technology, 2009, 23(2): 302-310

[7] ParkW. J., KimE. T., SongY. K., KoB. J.. A study on the real-time parameter estimation of DURUMI-II for control surface fault using flight test data [J]. International Journal of Control, Automation, and Systems, 2007, 5(4): 410-418

[8] ParkW. J., KimW. T., SeongK. J., KimY. C.. A study on the parameter estimation of DURUMI-II for the fixed right elevator using flight test data [J]. Journal of Mechanical Science and Technology, 2006, 20(8): 1224-1231

[9] KIM Y D. A study on fault detection and redundancy management system [R]. SUDP-P1-G4, March 2005.

[10] NapolitanoM. R., SongY. K., SeanorB.. On-line parameter estimation for restructurable flight control systems [J]. Aircraft Design, 2001, 4(1): 19-50

[11] MORELLI E A. Real-time parameter estimation in the frequency domain [C]// Proceedings of the 1999 AIAA Atmospheric Flight Mechanics Conference. Portland, Or., 1999. AIAA-99-4043.

[12] MORELLI E A. Identification of low order equivalent system models from flight test data [R]. NASA-TM-210117, 2000.

[13] SONG Y K. A study on real-time aircraft parameter estimation [C]// Proceedings of the KSAS Spring Annual Meeting. 2001: 359–362.

[14] PARK W J. A study on the design of real-time parameter estimator for an aircraft [D]. Hankuk Aviation University, 2004.

[15] HWANG M S, PARK W J, KIM Y C, EUN H B, CHOI W J, SONG Y K. Lateral stability improvement of a canard airplane using a vertical panel [C]// AIAA Atmospheric Flight Mechanics Conference and Exhibit. Monterey. California. 2002. AIAA-2002-4625.