A parameterized dynamics analysis model of legged lander with adaptive landing gear was established. Based on the analysis model, the landing performances under various landing conditions were analyzed by the optimized Latin hypercube experimental design method. In order to improve the landing performances, a hierarchical optimization method was proposed considering the uncertainty of landing conditions. The optimization problem was divided into a higher level (hereafter the "leader") and several lower levels (hereafter the "follower"). The followers took conditioning factors as design variables to fnd out the worst landing conditions, while the leader took bufer parameters as design variables to better the landing performance under worst conditions. First of all, sensitivity analysis of landing conditioning factors was carried out according to the results of experimental design. After the sensitive factors were screened out, the response surface models were established to refect the complicated relationships between sensitive conditioning factors, bufer parameters and landing performance indexes. Finally, the response surface model was used for hierarchical optimization iteration to improve the computational efciency. After selecting the optimum bufer parameters from the solution set, the dynamic model with the optimum parameters was simulated again under the same landing conditions as the simulation before. After optimization, nozzle performance against damage is improved by 5.24%, the acceleration overload is reduced by 5.74%, and the primary strut improves its performance by 21.10%.
Zongmao Ding
,
Hongyu Wu
,
Chunjie Wang
,
Jianzhong Ding
. Hierarchical Optimization of Landing Performance for Lander with Adaptive Landing Gear[J]. Chinese Journal of Mechanical Engineering, 2019
, 32(2)
: 20
-20
.
DOI: 10.1186/s10033-019-0331-0
A parameterized dynamics analysis model of legged lander with adaptive landing gear was established. Based on the analysis model, the landing performances under various landing conditions were analyzed by the optimized Latin hypercube experimental design method. In order to improve the landing performances, a hierarchical optimization method was proposed considering the uncertainty of landing conditions. The optimization problem was divided into a higher level (hereafter the "leader") and several lower levels (hereafter the "follower"). The followers took conditioning factors as design variables to fnd out the worst landing conditions, while the leader took bufer parameters as design variables to better the landing performance under worst conditions. First of all, sensitivity analysis of landing conditioning factors was carried out according to the results of experimental design. After the sensitive factors were screened out, the response surface models were established to refect the complicated relationships between sensitive conditioning factors, bufer parameters and landing performance indexes. Finally, the response surface model was used for hierarchical optimization iteration to improve the computational efciency. After selecting the optimum bufer parameters from the solution set, the dynamic model with the optimum parameters was simulated again under the same landing conditions as the simulation before. After optimization, nozzle performance against damage is improved by 5.24%, the acceleration overload is reduced by 5.74%, and the primary strut improves its performance by 21.10%.
[1] Schröder S, Reinhardt B, Brauner C, et al. Development of a Marslander with crushable shock absorber by virtual and experimental testing. Acta Astronautica, 2017, 134:65-74.
[2] Y Zhang, H Nie, J B Chen. Design and analysis of MR bumper about lunar damper soft landing. Aerospace Shanghai, 2009, 26(1):48-52. (in Chinese)
[3] G H Lucas, H D Robert, J M Veloria. Modeling and validation of a navy A6-intruder actively controlled landing gear system. NASA Langley Technical Report Server, 1999.
[4] J Holnickiszulc, P Pawłowski, M Mikułowski, et al. Adaptive impact absorption and applications to landing devices. Advances in Science & Technology, 2008, 56:609-613.
[5] M Ostrowski, J Holnicki-Szulc. Adaptive impact absorption controlled via pyrotechnic devices. 4th European Conf. on Structural Control, Petersburg, Russia, 2008.
[6] J H Hu. Research on magnetorheological fluid damping semi-active control system. Zhejiang University, 2007. (in Chinese)
[7] Q Zhou. Design and analysis of magneto rheological dynamic vibration absorber. Huazhong University of Science and Technology, 2013. (in Chinese)
[8] L Sa. Design of magnetorheological buffer for lunar lander soft landing gear. Beijing Jiaotong University, 2016. (in Chinese)
[9] B Y Niu. Structure design and optimization of magnetorheological buffer for lunar lander landing system. Chongqing University, 2016. (in Chinese)
[10] G M Mikulowski, J Holnickiszulc. Adaptive landing gear concept-feedback control validation. Smart Materials & Structures, 2007, 16(6):2146.
[11] A L Wang. Research on dynamics and semi-active control of lunar lander soft landing. Nanjing University of Aeronautics & Astronautics, 2011. (in Chinese)
[12] G Mikulowski, L Jankowski. Adaptive landing gear:Optimum control strategy and potential for improvement. Shock & Vibration, 2015, 16(2):175-194.
[13] T Maeda, M Otsuki, T Hashimoto, et al. Attitude stabilization for lunar and planetary lander with variable damper. Journal of Guidance, Control, and Dynamics, 2016:1790-1804.
[14] J J Wang, C J Wang, S G Song. Performance optimization of lunar lander based on response surface methodology. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(5):707-711. (in Chinese)
[15] H Y Wu, C J Wang, J Z Ding, et al. Soft landing performance optimization for novel lander based on multiple working conditions. Journal of Beijing University of Aeronautics and Astronautics, 2017(4):776-781. (in Chinese)
[16] Q X Qin, X Qin, J R Xiao, et al. Robust optimization design of the mars airbag lander. China Mechanical Engineering, 2017, 28(1):20-26. (in Chinese)
[17] J Z Yang, F M Zeng, J F Man, et al. Design and verification of the landing impact attenuation system for Chang'E-3 lander. Scientia Sinica (Technologica), 2014(5):440-449. (in Chinese)
[18] H Y Chai, Y H Deng, C Sheng. Design and realization of structure subsystem for the Chang'E-3 lunar lander. Scientia Sinica (Technologica), 2014(4):391-397. (in Chinese)
[19] X X Bai, N M Wereley, W Hu. Maximizing semi-active vibration isolation utilizing a magnetorheological damper with an inner bypass configuration. Journal of Applied Physics, 2015, 117(17):288.
[20] X X Bai, W Hu, N M Wereley. Magnetorheological damper utilizing an inner bypass for ground vehicle suspensions. IEEE Transactions on Magnetics, 2013, 49(7):3422-3425.
[21] A L Wang, H Nie, J B Chen. State-jump semi-active control of lunar lander soft landing. Acta Aeronautica Et Astronautica Sinica, 2009, 30(11):2218-2223. (in Chinese)
[22] Z W Li, Z J Li. Status of researching on dynamical models of MR damper. Machine Building & Automation, 2012, 41(1):142-145. (in Chinese)
[23] Y H Guo, E W Chen, Y M Lu, et al. Calculation of equivalent linear damping coefficient of a magnetorheological damper. China Mechanical Engineering, 2014, 25(13):1719-1723. (in Chinese)
[24] Z Q Deng, S C Wang, H B Gao, et al. Upper limit amplitude of lunar lander based on ADAMS software. Journal of Harbin Institute of Technology, 2003, 35(12):1492-1495. (in Chinese)
[25] "LORD Technical Data RD-8040-1 and RD-8041-1 Dampers, " Accessed on November 2015, www.lordfulfillment.com/upload/DS7016.pdf.
[26] R J Muraca, J W Campbell, C A King. A Monte Carlo analysis of the viking lander dynamics at touchdown. National Aeronautics and Space Administration, 1975.
[27] R E Lavender. Monte Carlo approach to touchdown dynamics for soft lunar landings. NASA-TN-D-3117, 1965.
