The ambiguous vibration characteristics of guns under multi-source strong excitations are the key technical bottlenecks that restrict the development of mobile firing guns with high firing accuracy. The development and challenges of nonlinear dynamic modeling and stabilization control of mobile firing guns such as tank guns are discussed and analyzed from three aspects: dynamic numerical simulation methods, dynamic characteristics under multi-source excitations and control methods of gun control systems. The current main problems existing in the research on dynamic modeling and stabilization control methods of mobile firing guns are discussed and summed up and the corresponding research points are proposed. The results of the analysis indicate that: To improve the firing accuracy of mobile firing guns, the characterization method of nonlinear factors in the system needs to be explored and test verified. The dynamic characteristics of guns under multi-source excitations need to be clarified and formed as an industry standard. More precise control methods with the targeted compensation strategy for the nonlinear factors of guns need to be designed.
DursunTBüyükcivelekFUtluÇ. A review on the gun barrel vibrations and control for a main battle tank. Def Technol2017; 13(5): 353–359.
2.
YangGGeJSunQ, et al. Development and application prospects of gun vibration and control. J Vib Meas Diagn2021; 41(6): 1043–1105.
3.
SunSWangBWuH. The development history and future prospects of naval gun weapons. J Gun Launch Contr2022; 43(1): 91–96.
4.
DursunTUtluÇÖzkanEN. Effects of tank gun structural components on the first shot hit probability. Def Sci J2018; 68(3): 273–281.
5.
DursunT. Effects of projectile and gun parameters on the dispersion. Def Sci J2020; 70(2): 166–174.
6.
DingYZhouKHeL, et al. Dynamic simulation and experiment of marching small unmanned ground vehicles with small arms. Arab J Sci Eng2023; 48(6): 8059–8073.
7.
LiuXYWuDLHouJ. Design and analysis of a scheme for the naval gun test shell entering the bore. Def Technol2021; 17(4): 1374–1386.
8.
WuBZhengJTianQT, et al. Friction and wear between rotating band and gun barrel during engraving process. Wear2014; 318(1–2): 106–113.
9.
RuiXWangXZhouQ, et al. Transfer matrix method for multibody systems (Rui method) and its applications. Sci China Technol Sci2019; 62(5): 712–720.
10.
RuiXZhangJWangX, et al. Multibody system transfer matrix method: the past, the present, and the future. Int J Mech Syst Dyn2022; 2: 3–26.
11.
DaxiniSDPrajapatiJM. Parametric shape optimization techniques based on meshless methods: a review. Struct Multidiscipl Optim2017; 56(5): 1197–1214.
12.
RohitGRPrajapatiJMPatelVB. Coupling of finite element and meshfree method for structure mechanics application: a review. Int J Comput Methods2020; 17(4): 1850151.
13.
ZhangBShiSYuS, et al. Establishment of a two-axis commercial vehicle 6DOF prediction model for nonlinear MPC controller. Proc IMechE, Part D: J Automobile Engineering2023. DOI: 10.1177/09544070231182181
14.
MiaoYWangGRuiX. Dynamics modeling, simulation, and optimization of vibration characteristics of the tracked vehicle system. J Vib Control2021; 27(21–22): 2451–2465.
15.
ZhouGWangYDuH. A generalized method for three-dimensional dynamic analysis of a full-vehicle model. Proc IMechE, Part D: J Automobile Engineering2020; 234(10–11): 2485–2499.
16.
TanBLiuKLiuH. Simulation of naval guns’ breechblock system dynamics based on ADAMS. In: Proceedings of the 2015 international conference on mechanical engineering and control systems (Mecs2015) World Scientific2016: pp. 445–448.
17.
Edward AlexanderJ. Advanced gun system gun and projectile dynamic model results and correlation to test data. J Press Vessel Technol ASME2012; 134(4): 041005.
18.
TzengJTSunW. Dynamic response of cantilevered rail guns attributed to Projectile/Gun Interaction—Theory. IEEE Trans Magn2007; 43(1): 207–213.
19.
LiuPShaoXZhouF, et al. A study on the application of the operating modal analysis method in self-propelled gun development. J Vibroengineering2016; 18(3): 1683–1691.
20.
ChenYYangGSunQ. Dynamic simulation on vibration control of marching tank gun based on adaptive robust control. J Low Freq Noise Vib Active Control2020; 39(2): 416–434.
21.
ShuklaJ. Dynamic analysis of gun control system of main battle tank. Int J Heavy Veh Syst2021; 28(2): 158–183.
22.
CaiJYuRYanQ, et al. Event-triggered adaptive control for tank gun control systems. IEEE Access2019; 7: 17517–17523.
23.
MaXSunG. Linear active disturbance rejection control for naval gun servo system. In: 37th Chinese control conference (CCC). IEEE, 2018: pp. 3971–3976.
24.
TiwariNPatilMShankarR, et al. Rigid body dynamics modeling, experimental characterization, and performance analysis of a howitzer. Def Technol2016; 12(6): 480–489.
25.
QianLFChenGS. The uncertainty propagation analysis of the projectile-barrel coupling problem. Def Technol2017; 13(4): 229–233.
26.
WangXRuiXWangJ, et al. Vibration characteristics analysis of tank gun barrel with non-uniform cross-section. Acta Mech Sin2022; 38(6): 521368.
27.
LiJSLiaoZQQiuM, et al. Analysis of arc-shaped support plate influence on muzzles vibration of gatling gun fire on tripod. Adv Mater Res2013; 712–715: 1464–1467.
28.
KeinänenHMoilanenSTervokoskiJ, et al. Influence of rotating band construction on gun tube loading—part I: numerical approach. J Press Vessel Technol2012; 134(4): 041006.
29.
YangYZhangXXuC, et al. Dynamic stress analysis of anisotropic gun barrel under coupled thermo-mechanical loads via finite element method. Lat Am J Solids Struct2020; 17(1): e243.
30.
YinDXiaoHLiB. Dynamics response of filament-wound composite barrel for rail gun with acceleration load. IEEE Trans Plasma Sci2018; 46(5): 1847–1854.
31.
WuDMaJDongZ. Vibration analysis of suspension system of self-propelled gun based on Adams. J Vib Shock2005; 24(5): 39–41.
32.
XuLYangGXieR. Modeling of three-dimensional road surface and analysis of vibration characteristics of self-propelled gun. J Ordnance Equip Eng2012; 33(8): 21–23.
33.
QianWWangL. Modelling and simulation of dynamics for the self propelled artillery running on the road. Acta Armamentarii2004; 25(5): 520–524.
34.
ZhouQBRuiXTWangGP, et al. An efficient and modular modeling for launch dynamics of tubed rockets on a moving launcher. Def Technol2021; 17(6): 2011–2026.
35.
JakatiABanerjeeSJebarajC. Development of mathematical models, simulating vibration control of tracked vehicle weapon dynamics. Def Sci J2017; 67(4): 465–475.
36.
RuiXRongBWangG, et al. Discrete time transfer matrix method for dynamics analysis of complex weapon systems. Sci China Technol Sci2011; 54(5): 1061–1071.
37.
RongBRuiXTaoL. Discrete time transfer matrix method for launch dynamics modeling and cosimulation of self-propelled artillery system. J Appl Mech2013; 80(1): 011008.
38.
XieRYangGXuL. Dynamic analysis of multi-body system for rigid-flexible coupling self-propelled gun on move. J Nanjing Univ Sci Technol2014; 38(5): 588–592.
39.
LiuFRuiXYuH, et al. Influence of barrels’ flexibility on the launch dynamics of tank during marching fire. J Vib Shock2016; 35(2): 58–63.
40.
XiaoHYangGSunQ. Research on flexible multi-body dynamics structure optimization of artilleries. Acta Armamentarii2017; 38(1): 27–34.
41.
XiaoHYangGGeJ. Surrogate-based multi-objective optimization of firing accuracy and firing stability for a towed artillery. J Vibroengineering2017; 19(1): 290–301.
42.
XieRYangGXuR, et al. Muzzle response of self-propelled antiaircraft gun on the move in consideration of clearance between trunnion and bearing. J Vib Shock2015; 34(16): 156–169.
43.
WangXRuiX. Dynamics modeling and simulation of tracked armored vehicle with planar clearance trunnion-bearing revolute joint. J Mech Sci Technol2021; 35(6): 2285–2302.
44.
XieRYangG. Dynamic analysis for self-propelled gun on the move with backlash nonlinearity between gear and arc. In: 2013 international forum on special equipments and engineering mechanics, 10–12 July 2013, Nanjing, China.
45.
ZhangJLiXTongH, et al. Dynamic contact non-linear calculation of elevating mechanism for infantry combat vehicle firing on the move. J Ballist2019; 31(3): 58–61.
46.
ChenYXieMJingX, et al. Dynamics simulation of naval gun servo system considering gear meshing. J Vib Shock2023; 42(20): 293–299.
47.
ChaturvediE. Numerical investigation of dynamic interaction with projectile and harmonic behaviour for T-finned machine gun barrels. Def Technol2020; 16(2): 460–469.
48.
KocMEsenICayY. Dynamic analysis of gun barrel vibrations due to effect of an unbalanced projectile considering 2-D transverse displacements of barrel tip using a 3-D element technique. Lat Am J Solids Struct2018; 15(9): e57.
49.
LinTQianLFYinQ, et al. Dynamic modeling and parameter identification of a gun saddle ring. Def Technol2020; 16(2): 325–333.
50.
DingCLiuNZhangX. A mesh generation method for worn gun barrel and its application in projectile-barrel interaction analysis. Finite Elem Anal Des2017; 124: 22–32.
51.
KeXWHouJWeiP. Dynamics analysis for naval gun with consideration of contact between arc and gear. Adv Mater Res2012; 479-481: 1535–1538.
52.
LiangCYangGGeJ, et al. Study on influence of structural arrangement of recoil mechanism on muzzle vibration of gun. Acta Armamentarii2013; 34(10): 1209–1214.
53.
GuoJDingHQiaoJ. Effect of rifling type on muzzle vibration of a large caliber gun-howitzer. J Ordnance Equip Eng2021; 42(4): 47–52.
54.
GastRMorrisSCostelloM. Simulation of shot impacts for the M1A1 tank gun. J Guid Control Dyn2000; 23(1): 53–59.
55.
OholRBParateBAThakurD. Plastic deformation of high explosive projectile 155 mm during gun launch conditions using finite element method. Def Sci J2022; 72(6): 793–800.
56.
HuaBBMaJSWuDL. Strength analysis of a naval gun bracket in marine combat conditions. Appl Mech Mater2011; 120: 393–396.
57.
NiuZLiH. Fatigue reliability research on key part of some naval gun. In: 2016 international conference on intelligent transportation, big data & smart city (ICITBS). IEEE, 2016, pp.592–596. DOI: 10.1109/icitbs.2016.141
58.
GuoYWangLZhaoF, et al. The restriction modal analysis of infantry combat vehicle auto-gun. In: Proceedings of 2015 IEEE 12th international conference on electronic measurement & instruments (ICEMI). IEEE, 2015, 3: pp.1158–1161.
59.
MaYZYangGLSunQQ, et al. Adaptive robust feedback control of moving target tracking for all - electrical tank with uncertainty. Def Technol2022; 18(4): 626–642.
60.
ChenYYangGZhouH, et al. Influence of projectile-barrel coupling on gun vibration of the moving tank under the influence of a stabilizer. Arab J Sci Eng2021; 46(8): 7635–7648.
61.
MaYYangGSunQ, et al. Adaptive robust control for tank stability: a constraint-following approach. Proc IMechE, Part I: J Systems and Control Engineering2021; 235(1): 3–14.
62.
YangMWangG. The building of naval gun dynamics simulation model based on Adams. In: Proceedings of the 3rd international conference on computer science and service system (CSSS). Atlantis Press, 2014: pp. 477–480.
63.
DiaoSZhaoYPengJ. Overall vibration analysis and structural parameter optimization of the naval gun system. J Gun Launch Contr2021; 42(1): 7–14.
64.
LiangCYangGWangX, et al. Study on influence of structural parameters on muzzle vibration of gun. In: 2013 international forum on special equipments and engineering mechanics, 10–12 July 2013, Nanjing, China.
65.
HeW. Vertical dynamics of a single-span beam subjected to moving mass-suspended payload system with variable speeds. J Sound Vib2018; 418: 36–54.
66.
SunQYangGGeJ. Modeling and simulation on engraving process of projectile rotating band under different charge cases. J Vib Control2017; 23(6): 1044–1054.
67.
AnguekOBounabB. Multi-objective design optimization of a turret’s U-bracket mounted on moving platform. Proc IMechE, Part C: J Mechanical Engineering Science2022; 236(24): 11371–11388.
68.
SongJBChoiSYParkK. Aiming error analysis of guns in ground combat vehicles operating on bumpy roads. J Mech Sci Technol2015; 29(12): 5145–5150.
69.
ChenYYangGSunQ. Dynamic simulation on nonlinear vibration of marching tank gun under high mobility conditions. Acta Armamentarii2019; 40(7): 1339–1348.
70.
WangGYaoLWeiL, et al. Research on the influence of linear vibration of a tank chassis on on-the-move firing accuracy. Acta Armamentarii2016; 37(3): 541–546.
71.
TrikandeMKarveNAnand RajR, et al. Semi-active vibration control of an 8x8 armored wheeled platform. J Vib Control2018; 24(2): 283–302.
72.
BanerjeeSBalamuruganVKrishna KumarR. Effect of integrated ride and cornering dynamics of a military vehicle on the weapon responses. Proc IMechE, Part K: J Multi-body Dynamics2018; 232(4): 536–554.
73.
BanerjeeSBalamuruganVKrishna KumarR. Vibration control of a military vehicle weapon platform under the influence of integrated ride and cornering dynamics. Proc IMechE, Part K: J Multi-body Dynamics2021; 235(2): 197–216.
74.
LiTWangRZhangJ, et al. Launch dynamic characteristics simulation analysis of vehicular Gatling gun in different vehicle speeds. J Vib Eng2014; 27(2): 186–192.
75.
LiuFFSongYMYuHL, et al. Study on the influence of projectile on muzzle disturbance. Def Technol2018; 14(5): 570–577.
76.
LiuFRuiXYuH, et al. Study on launch dynamics of the tank marching fire. J Shanghai Jiaotong Univ (Sci)2016; 21(4): 443–449.
77.
ChenYYangGLiuJ, et al. Dynamic bending of gun barrel during tank moving under multi-source excitation. J Vib Shock2022; 41(19): 16–21.
78.
ChenYYangGZhouH, et al. Sequential approximate optimization on projectile disturbances of the moving tank based on BP neural network. J Mech Sci Technol2021; 35(3): 935–944.
79.
ChenYXieMZouX, et al. Dynamic simulation on multilevel coupled vibration of a naval gun under foundation motion excitation of ship. Alex Eng J.
80.
ShenZ. Design and simulation of naval gun servo controller based on ADRC. In: 11th international conference on measuring technology and mechatronics automation (ICMTMA 2019). IEEE2019: pp. 345–349.
81.
TürkerK. Modeling and stabilization control of a main battle tank. Ankara: Middle East Technical University, 2011.
82.
ChenY. Research on comprehensive intelligent control technology of naval gun. J Gun Launch Contr2007; 105(1): 6–9.
83.
ChenYYangG. Dynamic simulation of tank stabilizer based on adaptive control. J Mech Eng Sci2019; 233(9): 3038–3049.
84.
GaoQHouRYangG, et al. Adjustment and control of a certain top-mounted gun based on a novel fractional order neural sliding mode strategy. Acta Armamentarii2013; 34(10): 1311–1317.
85.
JiDLiGYYangYP. Design of the naval gun digital servo system and its control tactics. Fire Contr Comm Contr2010; 35(9): 159–162+174. DOI: 1002-0640(2010) 09- 0159-04
86.
XianHYangWZhangW, et al. The application of dual-PID regulation based on sliding mode control in a tank artillery stabilizer. In: 4th international conference on intelligent computation technology and automation, 2011. IEEE, 2011, 1: pp. 731–733.
87.
GaoQYangGJiL, et al. A semi-adaptive fractional order PID control strategy for a certain gun control equipment. In: International conference on instrumentation, measurement, circuits and systems. ASME Press, 2012, pp. 223–226.
88.
GaoQChenJWangL, et al. Multiobjective optimization design of a fractional order PID controller for a gun control system. Sci World J2013; 2013(1): 907256–256.
89.
TianJYanQCaiJP, et al. The tracking problem in tank gun control systems with periodic reference signals. IEEE Access2020; 8: 132086–132094.
90.
LiFHaoJLiL, et al. Simulation of ship-borne rocket launcher servo system based on compound control. Fire Contr Comm Contr2022; 47(6): 121–125. DOI: 10.3969/j.issn.1002-0640.2022.06.019. (in Chinese)
91.
ZhengHRuiXZhangJ, et al. Research on active disturbance rejection control in stability control of tank gun system. In: 1st international conference on mechanical system dynamics (ICMSD 2022). IET, 2022, 2022: pp. 546–552
92.
LiCWangXSunQ, et al. Adaptive robust control of muzzle vibration for marching tank based on disturbance observer. In: 2022 international conference on advanced robotics and mechatronics (ICARM). IEEE, 2022: pp. 854–859
93.
JiangSTianFLiangW. Backlash compensation method in naval gun servo system based on global back-stepping sliding mode control. J Nav Univ Eng2018; 30(5): 92–98.
94.
WangZYangGWangX, et al. Adaptive–adaptive robust boundary control for uncertain mechanical systems with inequality constraints. Nonlinear Dyn2022; 110(1): 449–466.
95.
WangZFYangGLWangXY, et al. Adaptive robust control for triple avoidance - striking - arrival performance of uncertain tank mechanical systems. Def Technol2022; 18(8): 1483–1497.
96.
HongZYanQWuX, et al. Fuzzy system-based position tracking iterative learning control for tank gun control systems with error constraints. IEEE Access2022; 10: 52462–52471.
97.
WangHQiaoJ. Robust control research on adaptive wavelet neural network identification for tank all-electric gun control system. In: International conference on intelligent control and information processing. IEEE, 2011, 1: pp. 375–379
98.
GaoQSunZYangG, et al. A novel active disturbance rejection-based control strategy for a gun control system. J Mech Sci Technol2012; 26(12): 4141–4148.
99.
ZhengHRuiXZhangJ, et al. Nonlinear motor-mechanism coupling tank gun control system based on adaptive radial basis function neural network optimised computed torque controlISA Trans2022; 131: 222–235.
100.
WuYMaDLeG. Robust adaptive backstepping control for rocket launcher position servo system with constraint control. Acta Armamentarii2013; 34(4): 477–483. DOI: 10.3969/j.issn.1000-1093.2013.04.015.
101.
ZhangYXiaXLiF, et al. An adaptive fuzzy sliding mode position controller for naval gun servo system. Acta Armamentarii2015; 36(S2): 67–72. in Chinese.
102.
ZhuGWuXYanQ, et al. Robust learning control for tank gun control servo systems under alignment condition. IEEE Access2019; 7: 145524–145531.
103.
ChenYCaiYYangG, et al. Neural adaptive pointing control of a moving tank gun with lumped uncertainties based on dynamic simulation. J Mech Sci Technol2022; 36(6): 2709–2720.
104.
TianJQianLXuY, et al. Neural sliding mode control for tracking of axis of firepower of unmanned turret. Acta Armamentarii2011; 32(6): 641–645.
105.
LiCYangGWangX, et al. Adaptive robust target tracking control of marching tank under high-speed maneuvering condition. J Mech Sci Technol2022; 36(6): 2787–2798.
106.
ZhengHRuiXZhangJ, et al. Improved modeling and active disturbance rejection control of tank gun control system. J Syst Control Eng2022; 236(9): 1649–1666.
107.
YuanSYaoJDengW, et al. Active disturbance rejection adaptive control of tank turret-gun control systems. In: Proceedings of the 39th Chinese control conference (CCC). IEEE2020: pp. 333–339.
108.
XiaYDaiLFuM, et al. Application of active disturbance rejection control in tank gun control system. J Frankl Inst Appl Math2014; 351(4): 2299–2314.
109.
YeLXiaYFuM, et al. Active disturbance rejection control for gun control system of unmanned turret. IET Control Theory Appl2014; 31(11): 1580–1588.
110.
MaXYuanDLiK, et al. Series sliding mode control for gun control system based on extended state observer. Opt Precis Eng2011; 19(10): 2409–2418.
111.
SunQWangXYangG, et al. Robust pointing control of marching tank gun with matched and mismatched uncertainty. IEEE Trans Cybern2022; 52(8): 7303–7318.
112.
SunQWangXYangG, et al. Adaptive robust control for pointing tracking of marching turret-barrel systems: coupling, nonlinearity and uncertainty. IEEE Trans Intell Transp Syst2022; 23(9): 16397–16409.
113.
LinDWangXYangG, et al. Adaptive robust control for fully electric pitch system of tank with dynamic friction compensation. J Mech Sci Technol2022; 36(10): 4967–4978.
114.
MaXDengWXYuanSS, et al. Neural network based adaptive rise control of tank gun systems. J Phys Conf Ser2020; 1507: 052001.
115.
ZhangYYanQCaiJ, et al. Adaptive iterative learning control for tank gun servo systems with input deadzone. IEEE Access2020; 8: 63443–63451.
116.
ZhouZWangWZhangY, et al. Barrier adaptive iterative learning control for tank gun control systems under nonzero initial error condition. IEEE Access2022; 10: 8664–8672.
117.
YangQYanQCaiJ, et al. Neural network-based error-tracking iterative learning control for tank gun control systems with arbitrary initial states. IEEE Access2020; 8: 72179–72187.
118.
YuanDMaXWeiS, et al. Direct-transmission drive and dead time compensation control of tank gun control system. Electr Mach Control2016; 20(5): 111–118.
119.
ZhuGWuXCaiJ, et al. A barrier neuroadaptive dynamic surface control approach for tank gun control systems with input saturation. IEEE Access2023; 11: 43536–43545.
120.
YuanSDengWLiangX, et al. Nonlinear robust adaptive precision motion control of motor servo systems with unknown actuator backlash compensation. ISA Trans2023; 137: 349–357.
121.
YuanSSDengWXYaoJY, et al. Robust adaptive precision motion control of tank horizontal stabilizer based on unknown actuator backlash compensation. Def Technol2023; 20: 72–83.
122.
YuanSDengWGeY, et al. Nonlinear adaptive robust precision pointing control of tank servo systems. IEEE Access2021; 9: 23385–23397.
123.
LiWJiangJRenH, et al. Modeling and control of pointing-stabilizing-tracking system for marching guns. Acta Armamentarii2018; 39(8): 1479–1490.
124.
LiWHangCLiuA, et al. Modeling and simulation of self-stable gun line control using interference rate compensation. Acta Armamentarii2022; 43(6): 1233–1245.
125.
MaYYangGSunQ, et al. Hitting point tracking control of tank projectile based on Chebyshev exterior ballistic polynomial: an adaptive robust feedback approach. Acta Mech Sin2022; 38(4): 521234.
