Shimmy vibration control using robust model predictive control

A. Otmane Cherif

Abstract


Shimmy vibration is a very important common phenomenon in the landing gear system during either the take-off or landing of an aircraft. Shimmy vibration is the lateral and torsional vibrations in the wheel of the aircraft that is self-excited and causes instability in high speed performances which can damage the landing gear of the aircraft, its fuselage and even may result in hurting the passengers. In this paper, the aircraft landing gear shimmy dynamics model is studied with the following variable parameters; caster length, taxiing velocity and spring stiffness. The considered linearized landing gear system is a typical Linear Parameter Varying system, whose state-space matrices are functions of those varying parameters. The control objective is to steer the yaw angle to zero in order to suppress the shimmy when the landing gear system is subjected to uncertainties, which are varying taxiing velocity, and wheel caster length during landing; also, to rsional spring stiffness is considered as the probabilistic uncertain parameter. Therefore, both time-varying and probabilistic uncertain parameters are considered. Compared with two current robust model predictive controls, the proposed shimmy controller can effectively suppress the shimmy with more efficient computation. To verify the efficiency of the proposed algorithm, the simulation results are simulated by MATLAB software and its performance and efficiency are verified and discussed using comparative analysis.

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References


A. Otman sherif, D.V. Balandin, Robastnyj dizajn model'nogo prognoznogo upravlenija. Mezhdunarodnyj nauchnyj zhurnal «Sovremennye informacionnye tehnologii i IT-obrazovanie», [S.l.], v. 17, n. 4, dec. 2021. ISSN 2411-1473. Dostupno na: http://sitito.cs.msu.ru/index.php/SITITO/article/view/770.

M. Fallah, S. Long, W. Xie, and R. Bhat, Robust model predictive control of shimmy vibration in aircraft landing gears, Journal of Aircraft, vol. 45, no. 6, pp. 1872–1880, 2008.

I. Jocelyn et al., An overview of landing gear dynamics, 1999.

P. Baranyi, “Tp model transformation as a way to lmi-based controller design,” Industrial Electronics, IEEE Transactions on, vol. 51, no. 2, pp. 387–400, 2004.

G. Somieski, “Shimmy analysis of a simple aircraft nose landing gear model using different mathematical methods,” Aerospace Science and Technology, vol. 1, no. 8, pp. 545 – 555, 1997.

M. Morari and J. H. Lee, “Model predictive control: past, present and future,” Computers; Chemical Engineering, vol. 23, no. 45, pp. 667 – 682, 1999. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0098135498003019

S. P. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan, Linear matrix inequalities in system and control theory. Siam, 1994, vol. 15.

B. A. Smith, S. P. Kenny, and L. G. Crespo, “Probabilistic parameter uncertainty analysis of single input single output control systems,” NASA report, TM-2005-213280, 2005.

P. Baranyi, Y. Yam, D. Tikk, and R. J. Patton, “Trade-off between approximation accuracy and complexity: Ts controller design via hosvd based complexity minimization,” in Interpretability Issues in Fuzzy Modeling. Springer, 2003, pp. 249–277.

D. V. Balandin, M. M. Kogan An optimization algorithm for checking feasibility of robust H ∞-control problem for linear time-varying uncertain systems// International Journal of Control. 2004. V. 77. No. 5. P. 498-503.

D. V. Balandin, M. M. Kogan, Sintez optimal'nyh linejno-kvadratichnyh zakonov upravlenija na osnove linejnyh matrichnyh neravenstv, Avtomat. i telemeh, 2007. — 280 p. - ISBN 978-5-9221-0780-8.

P. Baranyi, A. R. V´arkonyi-K´oczy, Y. Yam, and R. J. Patton, “Adaptation of ts fuzzy models without complexity expansion: Hosvd-based approach,” Instrumentation and Measurement, IEEE Transactions on, vol. 54, no. 1, pp. 52–60, 2005.

M. V. Kothare, V. Balakrishnan, and M. Morari, “Robust constrained model predictive control using linear matrix inequalities,” Automatica, vol. 32, no. 10, pp. 1361–1379, 1996.

F. A. Cuzzola, J. C. Geromel, and M. Morari, “An improved approach for constrained robust model predictive control,” Automatica, vol. 38, no. 7, pp. 1183 – 1189, 2002.

N. Wada, K. Saito, and M. Saeki, “Model predictive control for linear parameter varying systems using parameter dependent lyapunov function,” in Circuits and Systems, 2004. MWSCAS’04. The 2004 47th Midwest Symposium on, vol. 3. IEEE, 2004, pp. iii–133.


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