焦宗夏1,2,4, 白宁1,2, 刘晓超2,4, 李珏菲1,2, 王壮壮1,2, 孙栋2,5, 齐鹏远2,3, 尚耀星1,2,4
收稿日期:
2022-05-06
修回日期:
2022-05-25
发布日期:
2022-07-08
通讯作者:
刘晓超,E-mail:liuxiaochaoustb@163.com
E-mail:liuxiaochaoustb@163.com
JIAO Zongxia1,2,4, BAI Ning1,2, LIU Xiaochao2,4, LI Juefei1,2, WANG Zhuangzhuang1,2, SUN Dong2,5, QI Pengyuan2,3, SHANG Yaoxing1,2,4
Received:
2022-05-06
Revised:
2022-05-25
Published:
2022-07-08
摘要: 机轮刹车系统是飞机上最重要的着陆减速系统,关系到飞机的安全起降,其核心是防滑刹车控制技术。飞机刹车过程包含了众多在控制领域具有挑战的问题(不确定性、强非线性和强时变性),如何在刹车过程中有效克服着陆中所涉及的地面摩擦、刹车盘力矩波动、起落架载荷变化和阵风等具有复杂非线性特征的干扰,实现对地面结合力的可控利用,将对提高飞机地面安全发挥重要作用。本文对飞机防滑刹车控制技术进行综述。简述了飞机机轮防滑刹车系统的作用、发展、基本控制原理和典型架构;从应用需求出发归纳了关键评价指标;以数学模型的形式描述了系统内的典型非线性环节和着陆环境中的扰动;按照飞机防滑控制技术发展的顺序,依次介绍讨论了开关式防滑控制、偏压调制式防滑控制、自适应防滑控制和智能防滑控制中具有代表性的方法。从刹车控制律验证角度介绍了全数字仿真和试验方法。最后,结合刹车控制系统研制所存在的问题与挑战对本领域所涉及的技术研究重点进行了展望。
中图分类号:
焦宗夏, 白宁, 刘晓超, 李珏菲, 王壮壮, 孙栋, 齐鹏远, 尚耀星. 飞机防滑刹车控制技术研究综述[J]. 航空学报, 2022, 43(10): 527384-527384.
JIAO Zongxia, BAI Ning, LIU Xiaochao, LI Juefei, WANG Zhuangzhuang, SUN Dong, QI Pengyuan, SHANG Yaoxing. Aircraft anti-skid braking control technology: A review[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(10): 527384-527384.
[1] KETABDARI M, TORALDO E, CRISPINO M. Numerical risk analyses of the impact of meteorological conditions on probability of airport runway excursion accidents[C]//Computational Science and Its Applications-ICCSA 2020, 2020:177-190. [2] KHAPANE P D. Simulation of asymmetric landing and typical ground maneuvers for large transport aircraft[J]. Aerospace Science and Technology, 2003, 7(8):611-619. [3] VATS S, HEENA A K, KAMAL H, et al. Preliminary study of aircraft braking system with emphasis on fail-safe technology[J]. Advances in Aerospace Science and Applications, 2013,3(3):191-198. [4] SHEVCHENKO A M. Energy-based approach for flight control systems design[J]. Automation and Remote Control, 2013, 74(3):372-384. [5] 赵兰浩, 孟庆堂, 郑楚良, 等. 民用飞机轮速传感器综述[J]. 民用飞机设计与研究, 2021(2):37-43. ZHAO L H, MENG Q T, ZHENG C L, et al. Review of civil aircraft wheel speed transducer[J]. Civil Aircraft Design & Research, 2021(2):37-43(in Chinese). [6] WAHI M K, WARREN S M, STRAUB H H. An extended prediction model for airplane braking distance and a specification for a total braking prediction systems[R]. Renton:Boeing Commercial Airplane Co., 1977. [7] MCCALLON L K. F-4 rain tire performance flight test[R]. 1974. [8] WAHI M K, WARREN S M, AMBERG R L, et al. Combat traction II, Phase II. Volume II, Detailed results of sensitivity study and prediction model calculations[R]. 1974. [9] LU J L, YUAN Z H, LIANG B. The adaptive control of aircraft brake based on asymmetric barrier Lyapunov function[C]//3rd International Conference on Electromechanical Control Technology and Transportation, 2018:102-109. [10] LIU Z H, LI Z S, QIN C, et al. The review and development of the brake system for civil aircrafts[C]//2016 IEEE International Conference on Aircraft Utility Systems. Piscataway:IEEE Press, 2016:762-767. [11] SIVARAMAKRISHNAN S, SINGH K B, LEE P. Influence of tire operating conditions on ABS performance[J]. Tire Science and Technology, 2015, 43(3):216-241. [12] PAPA G, TANELLI M, PANZANI G, et al. Wheel-slip estimation for advanced braking controllers in aircraft:model based vs. black-box approaches[J]. Control Engineering Practice, 2021, 117:104950. [13] TSENG H C, CHI C W. Aircraft antilock brake system with neural networks and fuzzy logic[J]. Journal of Guidance, Control, and Dynamics, 1995, 18(5):1113-1118. [14] LEE C, HEDRICK K, YI K. Real-time slip-based estimation of maximum tire-road friction coefficient[J]. IEEE/ASME Transactions on Mechatronics, 2004, 9(2):454-458. [15] AUSTIN L, MORREY D. Recent advances in antilock braking systems and traction control systems[J]. Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering, 2000, 214(6):625-638. [16] Crane Aerospace & Electronics. Antiskid systems[EB/OL].[2022-06-07]. https://www.craneae.com/antiskid-systems. [17] ACOSTA LÚA C, DI GENNARO S, SÁNCHEZ MORALES M E. Nonlinear adaptive controller applied to an Antilock Braking System with parameters variations[J]. International Journal of Control, Automation and Systems, 2017, 15(5):2043-2052. [18] TYUKIN I, PROKHOROV D, VAN LEEUWEN C. A new method for adaptive brake control[C]//Proceedings of the 2005 American Control Conference. Piscataway:IEEE Press, 2005:2194-2199. [19] LEE N J, KANG C G. Sliding mode control for wheel slide protection in railway vehicles with pneumatic brake systems[J]. International Journal of Precision Engineering and Manufacturing, 2017, 18(3):285-291. [20] ALY A A, ZEIDAN E S, HAMED A, et al. An antilock-braking systems (ABS) control:a technical review[J]. Intelligent Control and Automation, 2011, 2(3):186-195. [21] 陈元章. 电液压力伺服阀简介[J]. 机床与液压, 2021, 49(7):172-177. CHEN Y Z. Brief introduction of electro-hydraulic pressure servo valve[J]. Machine Tool & Hydraulics, 2021, 49(7):172-177(in Chinese). [22] 刘劲松, 周世民, 何学工, 等. 飞机刹车系统应用直接驱动伺服阀(DDV)的研究[J]. 航空精密制造技术, 2013, 49(2):48-51. LIU J S, ZHOU S M, HE X G, et al. Research on aircraft braking system by using direct drive servo valve[J]. Aviation Precision Manufacturing Technology, 2013, 49(2):48-51(in Chinese). [23] WU S, JIAO Z X, YAN L, et al. Development of a direct-drive servo valve with high-frequency voice coil motor and advanced digital controller[J]. IEEE/ASME Transactions on Mechatronics, 2014, 19(3):932-942. [24] 杨华勇, 王双, 张斌, 等. 数字液压阀及其阀控系统发展和展望[J]. 吉林大学学报(工学版), 2016, 46(5):1494-1505. YANG H Y, WANG S, ZHANG B, et al. Development and prospect of digital hydraulic valve and valve control system[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 46(5):1494-1505(in Chinese). [25] SUN D, JIAO Z X, SHANG Y X, et al. High-efficiency aircraft antiskid brake control algorithm via runway condition identification based on an on-off valve array[J]. Chinese Journal of Aeronautics, 2019, 32(11):2538-2556. [26] MOSELEY D D, CARTER T. Performance testing of an electrically actuated aircraft braking system[R]. 1988. [27] GEIGER M, MACY W, SKRIBLIS I. Demonstration of an electrically actuated brake with torque feedback[C]//Aerospace Atlantic Conference & Exposition. Warrendale:SAE International, 1996:91-96. [28] SAFRAN. Boeing 787 electric brake:an advanced technology that meets airline requirements[EB/OL]. (2017-06-22)[2022-06-07]. https://www.safran-landing-systems.com/media/boeing-787-electric-brake-advanced-technology-meets-airline-requirements. [29] 相里康. 飞机全电刹车力伺服控制与可靠驱动技术研究[D]. 西安:西北工业大学, 2018. XIANGLI K. Research on force servo control and reliable drive of aircraft electric braking system[D]. Xi'an:Northwestern Polytechnical University, 2018(in Chinese). [30] 张谦, 李兵强. 一种新型电静液作动飞机刹车系统[J]. 测控技术, 2011, 30(7):79-82. ZHANG Q, LI B Q. A novel electro-hydrostatic actuator for aircraft braking system[J]. Measurement & Control Technology, 2011, 30(7):79-82(in Chinese). [31] CURREY N S. Aircraft landing gear design:Principles and practices[M]. 1988. [32] 刘永军, 薛东青, 姜逸民. 某型民用飞机应急刹车系统权衡研究[J]. 科技资讯, 2010, 8(32):61-62. LIU Y J, XUE D Q, JIANG Y M. Trade study of the emergency braking system of a type of civil aircraft[J]. Science & Technology Information, 2010, 8(32):61-62(in Chinese). [33] SHANG Y X, LIU X C, JIAO Z X, et al. A novel integrated self-powered brake system for more electric aircraft[J]. Chinese Journal of Aeronautics, 2018, 31(5):976-989. [34] JIAO Z X, ZHANG H, SHANG Y X, et al. A power-by-wire aircraft brake system based on high-speed on-off valves[J]. Aerospace Science and Technology, 2020, 106:106177. [35] Federal Aviation Administration. Flight test guide for certification of transport category airplanes:AC No 25-7C[S]. 2012. [36] PRETAGOSTINI F, FERRANTI L, BERARDO G, et al. Survey on wheel slip control design strategies, evaluation and application to antilock braking systems[J]. IEEE Access, 2020, 8:10951-10970. [37] 严子林, 肖扬, 陆波. 民机刹车效率计算方法研究[J]. 科技视界, 2017(4):1-3. YAN Z L, XIAO Y, LU B. Study on anti-skid system efficiency of civil aircraft[J]. Science & Technology Vision, 2017(4):1-3(in Chinese). [38] CHANG Y P, GINDY M E, STREIT D A. Literature survey of transient dynamic response tyre models[J]. International Journal of Vehicle Design, 2004, 34(4):354. [39] MIKKOLA A. LuGre tire model for HMMWV[R]. 2014. [40] DUGOFF H. Tire performance characteristics affecting vehicle response to steering and braking control inputs. Final report[R]. 1969. [41] DUGOFF H, FANCHER P S, SEGEL L. An analysis of tire traction properties and their influence on vehicle dynamic performance[C]//International Automobile Safety Conference, 1970:1219-1243. [42] SVENDENIUS J, WITTENMARK B. Brush tire model with increased flexibility[C]//2003 European Control Conference (ECC), 2003:1863-1868. [43] LACOMBE J. Tire model for simulations of vehicle motion on high and low friction road surfaces[C]//2000 Winter Simulation Conference Proceedings, 2000:1025-1034. [44] MANCOSU F, SANGALLI R, CHELI F, et al. A new mathematical-physical 2D tire model for handling optimization on a vehicle[C]//International Congress & Exposition, 1999:1540-1547. [45] SAKAI H. Theoretical study of the effect of tractive and braking forces on cornering characteristics of tire[M]. 1969. [46] TIELKING J. A comparative evaluation of five tire traction models[R]. 1974. [47] FANCHER P, SEGEL L, MACADAM C, et al. Tire traction grading procedures as derived from the maneuvering characteristics of a tire-vehicle system. volumes I and II (combined)[R]. 1973. [48] BRACH R, BRACH M. The tire-force ellipse (friction ellipse) and tire characteristics[C]//SAE Technical Paper Series, 2011. [49] VELENIS E, TSIOTRAS P, CANUDAS-DE-WIT C. Extension of the LuGre dynamic tire friction model to 2D motion[C]//Proceedings of the 10th IEEE Mediterranean Conference on Control and Automation, 2002:9-12. [50] KIENCKE U, NIELSON L. Automotive control systems:for engine, driveline, and vehicle[J]. Measurement Science and Technology, 2000, 11(12):1828. [51] NICOLAS V T, COMSTOCK T R. Predicting directional behavior of tractor semitrailers when wheel anti-skid brake systems are used[C]//The American Society of Mechanical Engineers Winter Annual Meeting, 1972:1-12. [52] BAKKER E, NYBORG L, PACEJKA H B. Tyre modelling for use in vehicle dynamics studies[C]//SAE Technical Paper Series, 1987:190-204. [53] BOYLE S. Pacejka magic formula tire model parser[C]//2019 International Conference on Computational Science and Computational Intelligence (CSCI), 2019:517-518. [54] PACEJKA H B, BAKKER E. The magic formula tyre model[J]. Vehicle System Dynamics, 1992, 21:1-18. [55] NINAN S, SHETE V, NADKARNI I. FSTire:an open-source magic formula parameter estimation tool[J]. SAE International Journal of Vehicle Dynamics, Stability, and NVH, 2021, 5(1):3-13. [56] CANUDAS-DE-WIT C, TSIOTRAS P, VELENIS E, et al. Dynamic friction models for road/tire longitudinal interaction[J]. Vehicle System Dynamics, 2003, 39(3):189-226. [57] VAN ZANTEN A, RUF W D, LUTZ A. Measurement and simulation of transient tire forces[C]//SAE Technical Paper Series, 1989. [58] WU X D, ZUO S G, LEI L, et al. Parameter identification for a LuGre model based on steady-state tire conditions[J]. International Journal of Automotive Technology, 2011, 12(5):671-677. [59] CANUDAS DE WIT C, OLSSON H, ASTROM K J, et al. A new model for control of systems with friction[J]. IEEE Transactions on Automatic Control, 1995, 40(3):419-425. [60] DAHL P R. A solid friction model[R]. 1968. [61] PIATKOWSKI T. Dahl and LuGre dynamic friction models-The analysis of selected properties[J]. Mechanism and Machine Theory, 2014, 73:91-100. [62] CANUDAS-DE-WIT C, TSIOTRAS P. Dynamic tire friction models for vehicle traction control[C]//Proceedings of the 38th IEEE Conference on Decision and Control, 1999:3746-3751. [63] ALVAREZ L, YI J G. Adaptive emergency braking control in automated highway systems[C]//Proceedings of the 38th IEEE Conference on Decision and Control, 1999:3740-3745. [64] LIANG W, MEDANIC J, RUHL R. Analytical dynamic tire model[J]. Vehicle System Dynamics, 2008, 46(3):197-227. [65] HEINRICHS B E, ALLIN B D, BOWLER J J, et al. Vehicle speed affects both pre-skid braking kinematics and average tire/roadway friction[J]. Accident Analysis & Prevention, 2004, 36(5):829-840. [66] GATT A, BESSET S, JÉZÉQUEL L, et al. Reduction methods applied to aircraft brake squeal prediction and simulation[J]. Journal of Aircraft, 2016, 54(4):1340-1349. [67] GERDES J C, HEDRICK J K. Brake system requirements for platooning on an automated highway[C]//Proceedings of 1995 American Control Conference, 1995:165-169. [68] HAMZEH O N, TWORZYDLO W W, CHANG H J, et al. Analysis of friction-induced instabilities in a simplified aircraft brake[J]. SAE Transactions, 2000, 108(6):3404-3418. [69] 刘泽华, 谢彦. 基于变摩擦系数的飞机刹车系统仿真研究[J]. 航空科学技术, 2015, 26(4):33-38. LIU Z H, XIE Y. Simulating research of aircraft braking system based on friction coefficient changing[J]. Aeronautical Science & Technology, 2015, 26(4):33-38(in Chinese). [70] JIAO Z X, SUN D, SHANG Y X, et al. A high efficiency aircraft anti-skid brake control with runway identification[J]. Aerospace Science and Technology, 2019, 91:82-95. [71] 徐兴亚, 张立同, 成来飞, 等. 碳陶刹车材料的研究进展[J]. 航空制造技术, 2014, 57(6):100-103, 108. XU X Y, ZHANG L T, CHENG L F, et al. Research progress of carbon/silicon carbide brake materials[J]. Aeronautical Manufacturing Technology, 2014, 57(6):100-103, 108(in Chinese). [72] KUMAR P, SRIVASTAVA V K. Tribological behaviour of C/C-SiC composites-A review[J]. Journal of Advanced Ceramics, 2016, 5(1):1-12. [73] TANNER J A, STUBBS S M, DREHER R C, et al. Dynamics of aircraft antiskid braking systems[R]. 1982. [74] 曾小信. 飞机防滑刹车系统的建模与仿真研究[D]. 长沙:中南大学, 2008:35-36. ZENG X X. Modeling and simulation of aircraft brake system[D]. Changsha:Central South University, 2008:35-36(in Chinese). [75] 徐冬苓, 李玉忍, 谢利理. 飞机防滑刹车系统的建模与仿真研究[J]. 测控技术, 2004, 23(11):66-68. XU D L, LI Y R, XIE L L. Research on modeling and simulation of aircraft anti-skid braking system[J]. Measurement & Control Technology, 2004, 23(11):66-68(in Chinese). [76] KO H Y, HA D J, CHOI N Y. Optimal design of the aircraft ABS controller[J]. IFAC Proceedings Volumes, 2003, 36(8):219-224. [77] 陈勇, 黄华阳, 张健. 基于有限元法的飞机前起落架防摆刚度设计[J]. 成都大学学报(自然科学版), 2018, 37(4):419-421. CHEN Y, HUANG H Y, ZHANG J. Stiffness design of preventing front wheel shimmy based on FEM[J]. Journal of Chengdu University (Natural Science Edition), 2018, 37(4):419-421(in Chinese). [78] 王纪森, 汤传业, 邓英华, 等. 飞机防滑刹车系统动力学建模及仿真研究[J]. 计算机仿真, 2007, 24(10):70-73. WANG J S, TANG C Y, DENG Y H, et al. Dynamics modeling and simulation of aircraft ABS[J]. Computer Simulation, 2007, 24(10):70-73(in Chinese). [79] LERNBEISS R, PLÖCHL M. Simulation model of an aircraft landing gear considering elastic properties of the shock absorber[J]. Proceedings of the Institution of Mechanical Engineers, Part K:Journal of Multi-body Dynamics, 2007, 221(1):77-86. [80] SOMIESKI G. Shimmy analysis of a simple aircraft nose landing gear model using different mathematical methods[J]. Aerospace Science and Technology, 1997, 1(8):545-555. [81] GROSSMAN D T. F-15 nose landing gear shimmy, taxi test and correlative analyses[C]//SAE Technical Paper Series, 1980:3781-3791. [82] 张明, 吴晓宇. 飞机主起落架刹车诱导抖振分析[J]. 机械科学与技术, 2018, 37(11):1783-1790. ZHANG M, WU X Y. Analysis on brake induced vibration of aircraft main landing gear[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(11):1783-1790(in Chinese). [83] 李波, 焦宗夏. 飞机起落架系统动力学建模与仿真[J]. 北京航空航天大学学报, 2007, 33(1):46-49. LI B, JIAO Z X. Aircraft landing gear system dynamic modeling and simulation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(1):46-49(in Chinese). [84] QIU Y N, LIANG X G, DAI Z Y. Backstepping dynamic surface control for an anti-skid braking system[J]. Control Engineering Practice, 2015, 42:140-152. [85] CHEN M Q, XU F R, LIANG X L, et al. MSD-based NMPC aircraft anti-skid brake control method considering runway variation[J]. IEEE Access, 2021, 9:51793-51804. [86] LEMAY D, CHAMAILLARD Y, BASSET M, et al. Gain-scheduled yaw control for aircraft ground taxiing[J]. IFAC Proceedings Volumes, 2011, 44(1):12970-12975. [87] SATHISH S, SURYANARAYANAN L, JAIDEV VYAS J, et al. Applicability of tricycle modelling in the simulation of aircraft steering system[C]//Recent Advances in Theoretical, Applied, Computational and Experimental Mechanics, 2020:171-183. [88] HIRZEL E A. Antiskid and modern aircraft[C]//SAE Technical Paper Series, 1972. [89] GERARD M, PASILLAS-LÉPINE W, DE VRIES E, et al. Improvements to a five-phase ABS algorithm for experimental validation[J]. Vehicle System Dynamics, 2012, 50(10):1585-1611. [90] ARROWSMITH D, PLACE C M. An introduction to dynamical systems[M]. Cambridge:Cambridge University Press, 1990. [91] BOCCALETTI S, GREBOGI C, LAI Y C, et al. The control of chaos:theory and applications[J]. Physics Reports, 2000, 329(3):103-197. [92] LONBANI M A, MORANDINI M, ASTORI P, et al. Anti-skid braking control system design for aircraft:Multi-phase schemes approach[C]//20175th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, 2017:104-109. [93] PASILLAS-LÉPINE W. Hybrid modeling and limit cycle analysis for a class of five-phase anti-lock brake algorithms[J]. Vehicle System Dynamics, 2006, 44(2):173-188. [94] IVANOV V, SAVITSKI D, SHYROKAU B. A survey of traction control and antilock braking systems of full electric vehicles with individually controlled electric motors[J]. IEEE Transactions on Vehicular Technology, 2015, 64(9):3878-3896. [95] TANELLI M, OSORIO G, DI BERNARDO M, et al. Existence, stability and robustness analysis of limit cycles in hybrid anti-lock braking systems[J]. International Journal of Control, 2009, 82(4):659-678. [96] TANELLI M, OSORIO G, DI BERNARDO M, et al. Limit cycles analysis in hybrid anti-lock braking systems[C]//200746th IEEE Conference on Decision and Control, 2007:3865-3870. [97] VANTSEVICH V V, DEMKIV L I, KLOS S R, et al. An experimental study of longitudinal tire relaxation constants for vehicle traction dynamics modeling[C]//Proceedings of ASME 2019 Dynamic Systems and Control Conference, 2019. [98] HOSEINNEZHAD R, BAB-HADIASHAR A. Efficient antilock braking by direct maximization of tire-road frictions[J]. IEEE Transactions on Industrial Electronics, 2011, 58(8):3593-3600. [99] TUNAY I. Antiskid control for aircraft via extremum-seeking[C]//Proceedings of the 2001 American Control Conference, 2001:665-670. [100] STUBBS S M. Behavior of aircraft antiskid braking systems on dry and wet runway surfaces:a slip-velocity-controlled, pressure-bias-modulated system[M]. 1979. [101] VILLAUMÉ F. Brake-to-vacate system[M]. 2009. [102] LEIBER H, CZINCZEL A. Four years of experience with 4-wheel antiskid brake systems (ABS)[C]//SAE Technical Paper Series, 1983:423-430. [103] Aviation Safety Office of Civil Aviation Administration of China, Accident Investigation Center of Civil Aviation Administration of China. Cases of runway excursion/overrun in civil aviation of china[R]. Beijing:China Civil Aviation Press, 2015. [104] JIAO Z X, BAI N, SUN D, et al. A novel aircraft brake disturbance recognition model[J]. Aerospace Science and Technology, 2020, 107:106337. [105] JIAO Z X, WANG Z Z, SUN D, et al. A novel aircraft anti-skid brake control method based on runway maximum friction tracking algorithm[J]. Aerospace Science and Technology, 2021, 110:106482. [106] RATTASIRI W, WICKRAMARACHCHI N, HALGAMUGE S K. An optimized anti-lock braking system in the presence of multiple road surface types[J]. International Journal of Adaptive Control and Signal Processing, 2007, 21(6):477-498. [107] GHANDOUR R, VICTORINO A, DOUMIATI M, et al. Tire/road friction coefficient estimation applied to road safety[C]//18th Mediterranean Conference on Control and Automation, 2010:1485-1490. [108] ZHANG X W, XU Y, PAN M, et al. A vehicle ABS adaptive sliding-mode control algorithm based on the vehicle velocity estimation and tyre/road friction coefficient estimations[J]. Vehicle System Dynamics, 2014, 52(4):475-503. [109] YI J, ALVAREZ L, HOROWITZ R. Adaptive emergency braking control with underestimation of friction coefficient[J]. IEEE Transactions on Control Systems Technology, 2002, 10(3):381-392. [110] KISSAI M, MONSUEZ B, TAPUS A, et al. A new linear tire model with varying parameters[C]//20172nd IEEE International Conference on Intelligent Transportation Engineering, 2017:108-115. [111] AHN C, PENG H E, TSENG H E. Robust estimation of road frictional coefficient[J]. IEEE Transactions on Control Systems Technology, 2013, 21(1):1-13. [112] SINGH K B, TAHERI S. Estimation of tire-road friction coefficient and its application in chassis control systems[J]. Systems Science & Control Engineering, 2015, 3(1):39-61. [113] SINGH K B, ALI ARAT M, TAHERI S. An intelligent tire based tire-road friction estimation technique and adaptive wheel slip controller for antilock brake system[J]. Journal of Dynamic Systems, Measurement, and Control, 2013, 135(3):031002. [114] ARRICALE V M, MAIORANO A, MOSCONI L, et al. Improved anti-lock braking system with real-time friction detection to maximize vehicle performance[C]//Proceedings of ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2021. [115] YI J G, ALVAREZ L, CLAEYS X, et al. Emergency braking control with an observer-based dynamic tire/road friction model and wheel angular velocity measurement[J]. Vehicle System Dynamics, 2003, 39(2):81-97. [116] CANUDAS-DE-WIT C, PETERSEN M L, SHIRIAEV A. A new nonlinear observer for tire/road distributed contact friction[C]//42nd IEEE International Conference on Decision and Control, 2003:2246-2251. [117] YI J, ALVAREZ L, HOROWITZ R, et al. Adaptive emergency braking control using a dynamic tire/road friction model[C]//Proceedings of the 39th IEEE Conference on Decision and Control, 2000:456-461. [118] SHARIFZADEH M, TIMPONE F, FARNAM A, et al. Tyre-road adherence conditions estimation for intelligent vehicle safety applications[M]//Advances in Italian Mechanism Science, 2017:389-398. [119] MATSUTANI Y, SUGIYAMA H. On the parameter identification of LuGre tire friction model[C]//Proceedings of ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2014. [120] SHARIFZADEH M, AKBARI A, TIMPONE F, et al. Vehicle tyre/road interaction modeling and identification of its parameters using real-time trust-region methods[J]. IFAC-PapersOnLine, 2016, 49(3):111-116. [121] SAVITSKI D, IVANOV V, AUGSBURG K, et al. The new paradigm of an anti-lock braking system for a full electric vehicle:experimental investigation and benchmarking[J]. Proceedings of the Institution of Mechanical Engineers, Part D:Journal of Automobile Engineering, 2016, 230(10):1364-1377. [122] JIA J H, JIAO Z X, SUN D, et al. Aircraft anti-skid braking active disturbance rejection control based on optimal slip ratio[C]//CSAA/IET International Conference on Aircraft Utility Systems, 2018:1-6. [123] SAVITSKI D, SCHLEININ D, IVANOV V, et al. Robust continuous wheel slip control with reference adaptation:application to the brake system with decoupled architecture[J]. IEEE Transactions on Industrial Informatics, 2018, 14(9):4212-4223. [124] SATZGER C, DE CASTRO R. Predictive brake control for electric vehicles[J]. IEEE Transactions on Vehicular Technology, 2018, 67(2):977-990. [125] NÉMETH B, GÁSPÁR P, ORJUELA R, et al. LPV-based control design of an adaptive cruise control system for road vehicles[J]. IFAC-PapersOnLine, 2015, 48(14):62-67. [126] GAURKAR P V, CHALLA A, RAMAKRUSHNAN K, et al. Model predictive control of wheel slip towards antilock brake system using convex optimization[C]//2021 International Conference on COMmunication Systems & NETworkS, 2021:644-649. [127] TAVERNINI D, VACCA F, METZLER M, et al. An explicit nonlinear model predictive ABS controller for electro-hydraulic braking systems[J]. IEEE Transactions on Industrial Electronics, 2020, 67(5):3990-4001. [128] PATIL A, GINOYA D, SHENDGE P D, et al. Uncertainty-estimation-based approach to antilock braking systems[J]. IEEE Transactions on Vehicular Technology, 2016, 65(3):1171-1185. [129] DE CASTRO R, ARAÚJO R E, FREITAS D. Wheel slip control of EVs based on sliding mode technique with conditional integrators[J]. IEEE Transactions on Industrial Electronics, 2013, 60(8):3256-3271. [130] DU C L, LI F B, YANG C H, et al. Multiphase-based optimal slip ratio tracking control of aircraft antiskid braking system via second-order sliding-mode approach[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(2):823-833. [131] AMODEO M, FERRARA A, TERZAGHI R, et al. Wheel slip control via second-order sliding-mode generation[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(1):122-131. [132] HAMZAH N, ARIPIN M K, SAM Y M, et al. Second order sliding mode controller for longitudinal wheel slip control[C]//2012 IEEE 8th International Colloquium on Signal Processing and its Applications, 2012:138-143. [133] MOAVENI B, KHOSRAVI ROQAYE ABAD M, NASIRI S. Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter[J]. Vehicle System Dynamics, 2015, 53(10):1373-1392. [134] AMIRI M, MOAVENI B. Vehicle velocity estimation based on data fusion by Kalman filtering for ABS[C]//20th Iranian Conference on Electrical Engineering (ICEE2012), 2012:1495-1500. [135] GAO Y L, FENG Y, XIONG L. Vehicle longitudinal velocity estimation with adaptive Kalman filter[C]//Proceedings of the FISITA 2012 World Automotive Congress, 2013:415-423. [136] JIANG F J, GAO Z Q. An adaptive nonlinear filter approach to the vehicle velocity estimation for ABS[C]//Proceedings of the 2000 IEEE International Conference on Control Applications, 2000:490-495. [137] LI B Y, DU H P, LI W H. Comparative study of vehicle tyre-road friction coefficient estimation with a novel cost-effective method[J]. Vehicle System Dynamics, 2014, 52(8):1066-1098. [138] REZAEIAN A, KHAJEPOUR A, MELEK W, et al. Simultaneous vehicle real-time longitudinal and lateral velocity estimation[J]. IEEE Transactions on Vehicular Technology, 2017, 66(3):1950-1962. [139] REGOLIN E, ZAMBELLI M, FERRARA A. Wheel forces estimation via adaptive sub-optimal second order sliding mode observers[C]//2017 XXVI International Conference on Information, Communication and Automation Technologies, 2017:1-6. [140] M'SIRDI N K, RABHI A, FRIDMAN L, et al. Second order sliding mode observer for estimation of velocities, wheel sleep, radius and stiffness[C]//2006 American Control Conference, 2006. [141] TANELLI M, SAVARESI S M, CANTONI C. Longitudinal vehicle speed estimation for traction and braking control systems[C]//2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006:2790-2795. [142] SAVARESI S M, TANELLI M. Active braking control systems design for vehicles[M]. London:Springer London, 2010. [143] ONO E, ASANO K, SUGAI M, et al. Estimation of automotive tire force characteristics using wheel velocity[J]. Control Engineering Practice, 2003, 11(12):1361-1370. [144] SAVARESI S M, TANELLI M, CANTONI C. Mixed slip-deceleration control in automotive braking systems[J]. Journal of Dynamic Systems, Measurement, and Control, 2007, 129(1):20-31. [145] D'AVICO L, TANELLI M, SAVARESI S M, et al. An anti-skid braking system for aircraft via mixed-slip-deceleration control and sliding mode observer[C]//2017 IEEE 56th Annual Conference on Decision and Control, 2017:4503-4508. [146] CHEN M, GE S S, HOW B V E. Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities[J]. IEEE Transactions on Neural Networks, 2010, 21(5):796-812. [147] ELBRÄCHTER D, PEREKRESTENKO D, GROHS P, et al. Deep neural network approximation theory[J]. IEEE Transactions on Information Theory, 2021, 67(5):2581-2623. [148] EWERS B, BORDENEUVE-GUIBE J, GARCIA J P, et al. Expert supervision of an anti-skid control system of a commercial aircraft[C]//Proceedings of the 1996 IEEE International Symposium on Intelligent Control, 1996:420-425. [149] HARIFI A, RASHIDI F. Design of an adaptive fuzzy controller for antilock brake systems[J]. Automotive Science and Engineering, 2020, 10(1):3158-3166. [150] BELCHIOR C, ARAÚJO R, MENDES J, et al. H_{\\\\infty}$ adaptive fuzzy control approach applied to antilock-braking systems over a CAN network[C]//2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation, 2018:910-917. [151] KHAZAEI M, ROUHANI M. Fuzzy sliding mode controller for slip control of antilock brake systems[J]. Majlesi Journal of Electrical Engineering, 2016, 10(4):11. [152] LIN C M, HSU C F. Self-learning fuzzy sliding-mode control for antilock braking systems[J]. IEEE Transactions on Control Systems Technology, 2003, 11(2):273-278. [153] LIN C M, LI H Y. Intelligent hybrid control system design for antilock braking systems using self-organizing function-link fuzzy cerebellar model articulation controller[J]. IEEE Transactions on Fuzzy Systems, 2013, 21(6):1044-1055. [154] SOMAKUMAR R, CHANDRASEKHAR J. Intelligent anti-skid brake controller using a neural network[J]. Control Engineering Practice, 1999, 7(5):611-621. [155] CASTILLO J J, CABRERA J A, GUERRA A J, et al. A novel electrohydraulic brake system with tire-road friction estimation and continuous brake pressure control[J]. IEEE Transactions on Industrial Electronics, 2016, 63(3):1863-1875. [156] LEE H, TAHERI S. Intelligent Tires? A review of tire characterization literature[J]. IEEE Intelligent Transportation Systems Magazine, 2017, 9(2):114-135. [157] GARCIA-POZUELO D, OLATUNBOSUN O, YUNTA J, et al. A novel strain-based method to estimate tire conditions using fuzzy logic for intelligent tires[J]. Sensors (Basel, Switzerland), 2017, 17(2):350. [158] TUONONEN A, HARTIKAINEN L. Optical position detection sensor to measure tyre carcass deflections in aquaplaning[J]. International Journal of Vehicle Systems Modelling and Testing, 2008, 3(3):189. [159] TUONONEN A J. Optical position detection to measure tyre carcass deflections[J]. Vehicle System Dynamics, 2008, 46(6):471-481. [160] KUNO T, SUGIURA H. Detection of road conditions with CCD cameras mounted on a vehicle[J]. Systems and Computers in Japan, 1999, 30(14):88-99. [161] ALONSO J, LÓPEZ J M, PAVÓN I, et al. Platform for on-board real-time detection of wet, icy and snowy roads, using tyre/road noise analysis[C]//2015 International Symposium on Consumer Electronics, 2015:1-2. [162] KONGRATTANAPRASERT W, NOMURA H, KAMAKURA T, et al. Detection of road surface conditions using tire noise from vehicles[J]. IEEJ Transactions on Industry Applications, 2009, 129(7):761-767. [163] NISKANEN A J, TUONONEN A J. Three 3-axis accelerometers fixed inside the tyre for studying contact patch deformations in wet conditions[J]. Vehicle System Dynamics, 2014, 52(sup1):287-298. [164] NISKANEN A J, TUONONEN A J. Detection of the local sliding in the tyre-road contact by measuring vibrations on the inner liner of the tyre[J]. Measurement Science and Technology, 2017, 28(5):055007. [165] NISKANEN A J, XIONG Y, TUONONEN A J. Towards the friction potential estimation:a model-based approach to utilizing in-tyre accelerometer measurements[C]//2016 IEEE Intelligent Vehicles Symposium, 2016:625-629. [166] LIANG G Q, WANG Y, GARCIA M A, et al. A universal approach to tire forces estimation by accelerometer-based intelligent tire:analytical model and experimental validation[J]. Tire Science and Technology, 2022, 50(1):2-26. [167] WANG Y, LIU Z, KALISKE M, et al. Tire rolling kinematics model for an intelligent tire based on an accelerometer[J]. Tire Science and Technology, 2020, 48(4):287-314. [168] LENG B, DA J, XIONG L, et al. Estimation of tire-road peak adhesion coefficient for intelligent electric vehicles based on camera and tire dynamics information fusion[J]. Mechanical Systems and Signal Processing, 2021, 150:107275. [169] SINGH K B, ARAT M A, TAHERI S. Literature review and fundamental approaches for vehicle and tire state estimation[J]. Vehicle System Dynamics, 2019, 57(11):1643-1665. [170] LI L, YANG K, JIA G, et al. Comprehensive tire-road friction coefficient estimation based on signal fusion method under complex maneuvering operations[J]. Mechanical Systems and Signal Processing, 2015, 56-57:259-276. [171] KHALEGHIAN S, GHASEMALIZADEH O, TAHERI S. Estimation of the tire contact patch length and normal load using intelligent tires and its application in small ground robot to estimate the tire-road friction[J]. Tire Science and Technology, 2016, 44(4):248-261. [172] RIBEIRO A M, MOUTINHO A, FIORAVANTI A R, et al. Estimation of tire-road friction for road vehicles:a time delay neural network approach[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2019, 42(1):1-12. |
[1] | 陆亮, 夏飞燕, 訚耀保, 原佳阳, 方向. 小球式旋转直驱压力伺服阀动态特性分析优化[J]. 航空学报, 2018, 39(10): 422143-422143. |
[2] | 张明;聂宏. 飞机地面转弯和刹车响应动力学分析[J]. 航空学报, 2008, 29(3): 616-621. |
[3] | 李军;罗瑞盈;李强;毕燕洪. 飞机刹车盘用炭/炭复合材料新型防氧化复合涂层[J]. 航空学报, 2007, 28(6): 1494-1498. |
[4] | 田广来;谢利理;岳开宪;常顺宏;. 飞机防滑刹车系统的最佳滑移率式控制方法研究[J]. 航空学报, 2005, 26(4): 461-464. |
[5] | 何恒;吴瑞祥;黄伟明. 基于ANN与FNN的飞机防滑刹车系统设计[J]. 航空学报, 2005, 26(1): 116-120. |
[6] | 黄伟明;吴瑞祥;张燮年. 神经网络及模糊控制在飞机防滑刹车系统中的应用[J]. 航空学报, 2001, 22(4): 317-320. |
[7] | 张陵;诸德培;张瑜. 机轮制动力矩的变结构控制[J]. 航空学报, 1996, 17(5): 110-113. |
[8] | 张瑜;王纪森;史殿芸. 飞机数字式电子防滑系统采用新控制律的仿真研究[J]. 航空学报, 1995, 16(1): 124-128. |
[9] | 许希儒. 飞机电子防滑刹车系统模拟仿真[J]. 航空学报, 1993, 14(4): 219-222. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||
版权所有 © 航空学报编辑部
版权所有 © 2011航空学报杂志社
主管单位:中国科学技术协会 主办单位:中国航空学会 北京航空航天大学