The marine diesel engine propulsion system is a nonlinear system with time delay. In order to realize the accurate and real-time control of the marine diesel engine speed, a new method based on state-compensate extended state observer, backstepping method and beetle antennae search algorithm, that is, adaptive state-compensate extended state observer-backstepping, is proposed. First of all, the response relationship model between the engine speed and the fuel injection is established on the basis of the mean value model of diesel engine. Then, to deal with the load disturbances and model parameter perturbation of diesel engine, a state-compensate extended state observer is used to estimate lumped disturbances and states of the diesel engine, and a backstepping method combined with the state-compensate extended state observer, namely state-compensate extended state observer-backstepping, is used to control the marine diesel engine speed. Then, an adaptive state-compensate extended state observer-backstepping controller is proposed by introducing the beetle antennae search algorithm for online optimization of the control parameters. Finally, simulation experiments based on the model of the 12K98ME marine diesel engine are conducted to verify the effectiveness of the proposed controller under conditions of random disturbances, sudden dumping load and parameter perturbation. The experiment results show that the proposed adaptive state-compensate extended state observer-backstepping control method has a better control effect and stronger disturbance rejection ability in comparison of the standard linear active disturbance rejection control.
SinhaRPBalajiR.A mathematical model of marine diesel engine speed control system. J Inst Eng Chem Eng Div2018; 99: 63–70.
2.
BøTIJohansenTASrensenAJet al. Dynamic consequence analysis of marine electric power plant in dynamic positioning. Appl Ocean Res2016; 57: 30–39.
3.
XirosN. Robust control of diesel ship propulsion. London: Springer Science & Business Media, 2002.
4.
DuanHJZhuX.The application of a reduction-robust control algorithm to diesel engine speed control system. J Jilin Ins Chem Tech2004; 3: 52–54.
5.
ZhangLJMengJLanHet al. Robust L2 control design for speed regulation system of marine diesel engine generator. In: 8th world congress on intelligent control and automation, Jinan, China, 7–9 July 2010, pp.1656–1661. New York: IEEE.
6.
LiXAhmedQRizzoniG.Nonlinear robust control of marine diesel engine. J Mar Eng Technol2016; 16(1): 1–10.
7.
MalkhedeDNSethtB. Robust sliding mode controller for turbocharged diesel engine with parameter perturbations. In: Mediterranean conference on control & automation (MED ’07), Athens, 27–29 June 2007, pp.1–6. New York: IEEE.
8.
YuanYHeYCaiLet al. Discrete sliding mode variable structure control over the rotating speed of marine diesel engines. Proc IMechE, Part I: J Systems and Control Engineering2017; 231: 367–379.
9.
ChoiICJeungYCLeeDC. Variable speed control of diesel engine-generator using sliding mode control. In: IEEE transportation electrification conference and expo, Asia-Pacific, Harbin, China, 7–10 August 2017, pp.1–5. New York: IEEE.
10.
KangEHongSSunwooM.Idle speed controller based on active disturbance rejection control in diesel engines. Int J Automot Techn2016; 17(6): 937–945.
11.
GuoJLiangSChenG. Application of CMAC neural network & PID control on the speed control system of diesel engine. In: 6th world congress on intelligent control and automation, Dalian, China, 21–23 June 2006, pp.2840–2844. New York: IEEE.
12.
ShenXQSuYX.Marine diesel engine speed control system based on fuzzy-PID. Appl Mech Mater2012; 152–154: 1589–1594.
13.
TangJRLeiYYNieGWet al. Application of PID neural network in control of diesel engine speed. Coal Mine Mach2010; 1: 201–204.
14.
WangCSZhouYBPanWGet al. The application of ADRC in the ship main engine speed controller based on genetic algorithm. Adv Mater Res2011; 327: 17–22.
15.
WangFZouQHuaCet al. Disturbance observer-based dynamic surface control design for a hypersonic vehicle with input constraints and uncertainty. Proc IMechE, Part I: J Systems and Control Engineering2016; 230(6): 522–536.
16.
FengHGuoBZ.Active disturbance rejection control: old and new results. Annu Rev Control2017; 44: 238–248.
17.
GuoBZ.Active disturbance rejection control: from ODEs to PDEs. IFAC PapersOnline2016; 49(8): 278–283.
18.
ShaoXLWangHL.Performance analysis on linear extended state observer and its extension case with higher extended order. Control Decis2015; 30: 815–822.
19.
WangLJTongCNLiQet al. A practical decoupling control solution for hot strip width and gauge regulation based on active disturbance rejection. Control Theory Appl2012; 29(11): 1471–1478.
20.
GaoZ.Scaling and bandwidth-parameterization based controller tuning. In: Proceedings of the American control conference, Denver, CO, 4–6 June 2003, pp.4989–4996. New York: IEEE.
21.
ZhangQWangZ.Based on active disturbance rejection controller for diesel engine speed control. J Electron Test2012(12): 15–19.
22.
Yu-DongLIDa-BinHUXiaJ.Application of ADRC in speed regulation system of diesel engine. Ship Sci Technol2010; 8(8): 221–227.
23.
LiSYangJChenWHet al. Generalized extended state observer based control for systems with mismatched uncertainties. IEEE T Ind Electron2012; 59(12): 4792–4802.
24.
LiuCNegenbornRRZhengHet al. A state-compensation extended state observer for model predictive control. Eur J Control2017; 36: 1–9.
25.
ZhaoJSunXZhaoLet al. Robust backstepping control of double-rod cylinder for motion synchronization of mold oscillator. Proc IMechE, Part I: J Systems and Control Engineering2018; 232(1): 29–38.
26.
ZhouCZhuJLeiHet al. Robust constraint backstepping control for high-performance aircraft with account of unsteady aerodynamic effects. Proc IMechE, Part G: J Aerospace Engineering2016; 230(13): 2484–2503.
27.
ZhangXKZhangQRenHXet al. Linear reduction of backstepping algorithm based on nonlinear decoration for ship course-keeping control system. Ocean Eng2018; 147: 1–8.
28.
ChenXTTanWW.Tracking control of surface vessels via adaptive type-2 fuzzy logic control. Ocean Eng2013; 70(4): 97–109.
29.
DongZWanLLiYet al. Trajectory tracking control of underactuated USV based on modified backstepping approach. Int J Nav Arch Ocean2015; 7(5): 817–832.
30.
ZhangQJiangNHuYet al. Design of course-keeping controller for a ship based on backstepping and neural networks. Int J e-Navigat Maritime Control2017; 7: 34–41.
31.
XieSChuXLiuCet al. Ship heading control based on backstepping and least squares support vector machine. In: International conference on transportation information and safety, Banff, AB, Canada, 8–10 August 2017, pp.196–203. New York: IEEE.
MuliadiJKusumoputroB.Neural network control system of UAV altitude dynamics and its comparison with the PID control system. J Adv Transport2018; 2018: 3823201.
34.
VijayMJenaD.PSO based neuro fuzzy sliding mode control for a robot manipulator. J Electr Syst Inf Technol2017; 4(1): 243–256.
35.
BingulZKarahanO.Comparison of PID and FOPID controllers tuned by PSO and ABC algorithms for unstable and integrating systems with time delay. Optim Contr Appl Met2018; 39(4): 1431–1450.
36.
JiangXLiS.Beetle antennae search without parameter tuning (BAS-WPT) for multi-objective optimization. arXiv preprint arXiv:1711.02395, 2017.
TuHChenH.A numerical study on the performance and emission of a container ship propulsion system. Int J Comput Appl T2016; 53(3): 244–254.
39.
TheotokatosG.On the cycle mean value modelling of a large two-stroke marine diesel engine. Proc IMechE, Part M: J Engineering for the Maritime Environment2010; 224(3): 193–205.
40.
TuHChenH.Linear active disturbance rejection control for marine diesel engine. Ship Eng2016; 38(3): 31–36.
41.
PanWXiaoH.Design of diesel engine adaptive active disturbance rejection speed controller. J Open Autom Control Syst2015; 7(1): 1429–1433.
42.
HanJ.From PID to active disturbance rejection control. IEEE T Ind Electron2009; 56(3): 900–906.
43.
TaskarBSteenSBensowREet al. Effect of waves on cavitation and pressure pulses. Appl Ocean Res2016; 60: 61–74.
