This paper presents a new model-free adaptive full-order sliding mode control (MAFOSMC) approach for addressing the challenge of precise control for the high-pressure common rail system (HPCRS) in marine engines. First, the mathematical model of HPCRS is modeled based on the hydrodynamics and the problem statement is presented. The model-free control structure is designed by adopting time delay control (TDC) technology, which can estimate uncertain and unknown dynamics without exact priori information about the system. Furthermore, the continuous sliding mode controller is developed to exhibit features of high accuracy, strong robustness, fast response based on full-order sliding mode control (FOSMC), and improved power reaching law. Then, a bidirectional adaptive strategy was designed to handle the unmodelled dynamics and unknown disturbances. The stability analysis of the closed-loop system is conducted using Lyapunov theory. Overall, the experimental comparisons were conducted with traditional FOSMC under three different testing scenarios, validating the efficacy and benefits of the proposed MAFOSMC approach for marine engines.
AhmedSAzarAT (2024) Adaptive fractional tracking control of robotic manipulator using fixed-time method. Complex & Intelligent Systems10(1): 369–382.
2.
AhmedSGhousI (2022) TDE based model-free control for rigid robotic manipulators under nonlinear friction. Scientia Iranica3: 85–97.
3.
AhmedSWangHTianY (2021) Adaptive high-order terminal sliding mode control based on time delay estimation for the robotic manipulators with backlash hysteresis. IEEE Transactions on Systems, Man, and Cybernetics: Systems51(2): 1128–1137.
4.
AhmedSAzarATTounsiM, et al. (2023) Adaptive control design for Euler–Lagrange systems using fixed-time fractional integral sliding mode scheme. Fractal and Fractional7(10): 712.
5.
BaekJChoSHanS (2018) Practical time-delay control with adaptive gains for trajectory tracking of robot manipulators. IEEE Transactions on Industrial Electronics65(7): 5682–5692.
6.
BalluchiABicchiAMazziE, et al. (2007) Hybrid modelling and control of the common rail injection system. International Journal of Control80(11): 1780–1795.
7.
CataniaAEFerrariAMannoM, et al. (2008) Experimental investigation of dynamics effects on multiple-injection common rail system performance. Journal of Engineering for Gas Turbines & Power130(3): 032806–032819.
8.
ChenHGongXLiuQ, et al. (2014) Triple-step method to design non-linear controller for rail pressure of gasoline direct injection engines. IET Control Theory & Applications8(11): 948–959.
9.
FengYYuXHManZH (2002) Non-singular terminal sliding mode control of rigid manipulators. Automatica38(12): 2159–2167.
FerrariAPaolicelliF (2018) Modal analysis of fuel injection systems and the determination of a transfer function between rail pressure and injection rate. Journal of Engineering for Gas Turbines & Power140(11): 112808–112819.
12.
GaoYWangL (2023) Broad bandgap active metamaterials with optimal time-delayed control. International Journal of Mechanical Sciences254: 108449.
13.
GaoZGLiHMXuCL, et al. (2022) Control strategy based on flow conservation equation for high-pressure common rail system. International Journal of Automotive Technology23(3): 793–803.
14.
GuoJLiuYZhouJ (2019) New adaptive sliding mode control for a mismatched second-order system using an extended disturbance observer. Transactions of the Institute of Measurement and Control41(1): 276–284.
15.
HongSShinJSohnJ, et al. (2015) Coordinated control strategy for the common-rail pressure using a metering unit and a pressure control valve in diesel engines. Proceedings of the Institution of Mechanical Engineers - Part D: Journal of Automobile Engineering229(7): 898–911.
16.
HosokawaAMitsuhashiYSatohK, et al. (2023) Output feedback full-order sliding mode control for a three-tank system. ISA Transactions133: 184–192.
17.
JiZXieXSunZ, et al. (2011) Rail pressure control of common rail diesel engine based on RBF neural network adaptive PID controller. In: Proceedings of 2011 international conference on electronic & mechanical engineering and information technology, Harbin, China, 12–14 August 2011, pp. 1122–1125.
18.
JinMKimJLeeJ, et al. (2017) Improving time-delay control for robot manipulators using tsk fuzzy logic control systems. In: IEEE ASME international conference on advanced intelligent mechatronics. Munich, Germany, 3–7 July 2017, 1743–1748.
19.
KaliYSaadMBenjellounK, et al. (2017) Discrete-time second order sliding mode with time delay control for uncertain robot manipulators. Robotics and Autonomous Systems94: 53–60.
20.
KaliYSaadMBenjellounK, et al. (2018) Super-twisting algorithm with time delay estimation for uncertain robot manipulators. Nonlinear Dynamics93(2): 557–569.
21.
LevantA (2003) Higher-order sliding modes, differentiation and output-feedback control. International Journal of Control76: 924–941.
22.
LevantA (2007) Principles of 2-sliding mode design. Automatica43(4): 576–586.
23.
LiHZhangS (2018) Research on high voltage common rail pressure optimization based on iterative neural dynamic programming data driven. In: 2018 37th Chinese control conference, Wuhan, China, 25–27 July 2018, pp. 8002–8007.
24.
LingJLiJWangX, et al. (2020) Research on ADRC based control algorithm of common rail pressure for diesel engines. In: 2020 IEEE international conference on artificial intelligence and information systems (ICAIIS), Dalian, China, 20–22 March 2020, pp. 656–660.
25.
LinoPMaioneBRizzoA (2007) Nonlinear modelling and control of a common rail injection system for diesel engines. Applied Mathematical Modelling31(9): 1770–1784.
26.
LiuQChenHHuY, et al. (2014) Modeling and control of the fuel injection system for rail pressure regulation in GDI engine. IEEE-ASME Transactions on Mechatronics19(5): 1501–1513.
27.
LiuJSunMChenZ, et al. (2020) Super-twisting sliding mode control for aircraft at high angle of attack based on finite-time extended state observer. Nonlinear Dynamics99(4): 2785–2799.
28.
MaCSongEZYaoC, et al. (2021) Analysis of PPCI mode and multi-objective comprehensive optimization for a dual-fuel engine. Fuel303(1): 121296.
29.
MaCSongEZYaoC, et al. (2022) Multi-objective optimization of dual-fuel engine performance in PPCI mode based on preference decision. Fuel312(15): 122901.
30.
MirzaeiMJMoosapourSHAslmostafaE, et al. (2023) Finite time super twisting controller based on adaptive dual-layer disturbance observer for synchronisation of nonlinear chaotic systems. International Journal of Control96(10): 2477–2489.
31.
MobayenS (2015) An adaptive fast terminal sliding mode control combined with global sliding mode scheme for tracking control of uncertain nonlinear third-order systems. Nonlinear Dynamics82(1–2): 599–610.
32.
MobayenSKaramiHFekihA (2021) Adaptive nonsingular integral-type second order terminal sliding mode tracking controller for uncertain nonlinear systems. International Journal of Control, Automation and Systems19(4): 1539–1549.
33.
PimaoLYoutongZTieshuanL, et al. (2015) Elimination of fuel pressure fluctuation and multi-injection fuel mass deviation of high pressure common-rail fuel injection system. Chinese Journal of Mechanical Engineering28(2): 294–306.
34.
RabieeHAtaeiMEkramianM (2019) Continuous nonsingular terminal sliding mode control based on adaptive sliding mode disturbance observer for uncertain nonlinear systems. Automatica109: 108515.
35.
RoyTKMahmudMANasiruzzamanABM, et al. (2021) A non-singular fast terminal sliding mode control scheme for residual current compensation inverters in compensated distribution networks to mitigate powerline bushfires. IET Generation, Transmission & Distribution15(9): 1421–1434.
36.
SunYZhangL (2021) Fixed-time adaptive fuzzy control for uncertain strict feedback switched systems. Information Sciences546: 742–752.
37.
SunYChenBLinC, et al. (2018) Finite-time adaptive control for a class of nonlinear systems with nonstrict feedback structure. IEEE Transactions on Cybernetics48(10): 2774–2782.
38.
UtkinV (2013) On convergence time and disturbance rejection of super-twisting control. IEEE Transactions on Automatic Control58(8): 2013–2017.
39.
WangHPZhengDTianY (2016a) High pressure common rail injection system modeling and control. ISA Transactions63: 265–273.
40.
WangHPTianYZhengD (2016b) ESO-based iPI common rail pressure control of high pressure common rail injection system. Studies in Informatics and Control25(3): 273–282.
41.
WangJSunHDaiC, et al. (2019a) GPIO-based rail pressure control for diesel high pressure common rail injection system. Journal of Engineering2019(22): 8293–8298.
42.
WangYZhuKYanF, et al. (2019b) Adaptive super-twisting nonsingular fast terminal sliding mode control for cable-driven manipulators using time-delay estimation. Advances in Engineering Software128: 113–124.
43.
XieSChenQ (2022) Adaptive nonsingular predefined-time control for attitude stabilization of rigid spacecrafts. IEEE Transactions on Circuits and Systems II: Express Briefs69(1): 189–193.
44.
XiuCGuoP (2018) Global terminal sliding mode control with the quick reaching law and its application. IEEE Access6: 49793–49800.
45.
YanXEstradaAPlestanF (2016) Adaptive pulse output feedback controller based on second-order sliding mode: methodology and application. IEEE Transactions on Control Systems Technology24(6): 2233–2240.
46.
YoonMLeeKSunwooM (2007) A method for combustion phasing control using cylinder pressure measurement in a CRDI diesel engine. Mechatronics17(9): 469–479.
47.
Youcef-ToumiKItoO (1988) A time delay controller for systems with unknown dynamics. In: 1988 American control conference, Atlanta, GA, 15–17 June 1988, 904–913.
48.
YuanZDaiCSunH, et al. (2023) GPIO based sliding mode control for diesel engine high pressure common rail system. International Journal of Automotive Technology24(1): 147–158.
