To improve handling and stability for distributed drive electric vehicles (DDEV), the study on four wheel steering (4WS) systems can improve the vehicle driving performance through enhancing the tracking capability to desired vehicle state. Most previous controllers are either a large amount of calculation, or requires a lot of experimental data, these are relatively time-consuming and laborious. According to the front and rear wheel steering angle of DDEV can be distributed independently, a novel controller named internal model controller with fractional-order filter (IMC-FOF) for 4WS systems is proposed and studied in this paper. The IMC-FOF is designed using the internal model control theory and compared with IMC and PID controller. The influence of time constant and fractional-order parameters which is optimized using quantum genetic algorithms (QGA) on tracking ability of vehicle state are also analyzed. Using a production vehicle as an example, the simulation is performed combining Matlab/Simulink and CarSim. The comparison results indicated that the proposed controller presents performance to distribute the front and rear wheel steering angle for ensuring better tracking capability to desired vehicle state, meanwhile it possesses strong robustness.
ZhangBJ.Study on lateral dynamics characters and control of 4WS vehicle. MA Thesis, Tianjin University, China, 2006.
2.
AlexandruC.A mechanical integral steering system for increasing the stability and handling of motor vehicles. Proc IMechE, Part C: J Mechanical Engineering Science2015; 231: 1465–1480.
3.
NamKKimYOhS, et al. Steering Angle-Disturbance observer (SA-DOB) based yaw stability control for electric vehicles with in-wheel motors. In: International Conference on Control Automation and System (ICCAS 2010). Gyeonggi-do, South Korea, 27–30 October 2010, pp.1303–1307.
4.
AriffMHMZamzuriHNordinMAM, et al. Optimal control strategy for low speed and high speed four-wheel-active steering vehicle. J Mech Eng Sci2015; 8: 1516–1528.
5.
LvHMChenNLiP.Multi-objective H∞ optimal control for four-wheel steering vehicle based on yaw rate tracking. Proc IMechE, Part D: J Automobile Engineering2004; 218: 1117–1123.
6.
QiZJYangZGHuangY.Lane change track control for intelligent 4WS vehicle based on fuzzy adaptive PID. Chin J Automot Eng2012; 2: 379–384.
7.
YuJBHanZN.Fuzzy PID control for 4WS vehicle based on model tracking technology. J Chin Agric Mech2013; 34: 188–192.
8.
GaoLJinLZhengY, et al. Design of radial basis function neural network compound controller for four wheel steering vehicle. J Jilin Univ2016; 46: 366–372.
9.
WangJYuSYChenH.Model following control of active 4WS vehicle based on constrained output feedback H∞ control. Inf control2016; 45: 53–59.
10.
YinGDChenNLiP.Improving handling stability performance of four-wheel steering vehicle via μ-synthesis robust control. IEEE Trans Veh Technol2007; 56: 2432–2439.
11.
HiranoYFukataniK.Development of robust active rear steering control for automobile. Trans Jpn Soc Mech Eng2008; 62: 231–238.
12.
YinGChenNWangJ, et al. Robust control for 4WS vehicles considering a varying tire-road friction coefficient. Int J Automot Technol2010; 11: 33–40.
13.
KazemiMShiraziKH.Handling enhancement of a sliding-mode control assisted four-wheel steer vehicle. Proc IMechE, Part D: J Automobile Engineering2012; 226: 234–246.
14.
MarinoRCiniliF. Input-output decoupling control by measurement feedback in four-wheel-active-steering vehicles. In: Proceedings of the 45th IEEE Conference on Decision and Control, San Diego, CA, 13–15 December, 2006, pp.1715–1720. New York: IEEE.
15.
LiMXJiaYMDuJP.LPV control with decoupling performance of 4WS vehicles under velocity-varying motion. IEEE Trans Control Syst Technol2014; 22: 1708–1724.
16.
WangSFLiHS. Integrated rear wheel steering angle and yaw moment optimal control of four-wheel-steering vehicle. In: IEEE 2010 Chinese Control and Decision Conference (CCDC), Xuzhou, China, 26–28 May, 2010, pp.2490–2493. New York: IEEE.
17.
LiMXXuHJJiaYM.Parameter optimization for decoupling controllers of 4WS vehicles. Artif Life Rob2013; 18: 64–69.
18.
LiMXJiaYM.Precompensation decoupling control with H∞ performance for 4WS velocity-varying vehicles. Int J Syst Sci2016; 47: 3864–3875.
19.
HajjajiAECiocanAHamadD.Four wheel steering control by fuzzy approach. J Intell Rob Syst2005; 41: 141–156.
20.
Jazar and RezaN. Vehicle dynamics: theory and application. Boston, MA: Springer, 2008, pp.631-633.
21.
YuZS.Vehicle theory. Beijing: China Machine Press, 1990, pp.144–146.
TianR.Four-wheel steering and direct yaw moment control. MA Thesis, Hefei University of Technology, China, 2018.
24.
MaamarBRachidM.IMC-PID-fractional-order-filter controllers design for integer order systems. ISA Trans2014; 53: 1620–1628.
25.
HemavathyPRMohamedSYLakshmanaprabuSK.Internal model controller based PID with fractional filter design for a nonlinear process. Int J Electr Comput Eng2020; 10: 243–254.
26.
ChekariTMansouriRBettayebM.IMC-PID fractional order filter multi-loop Controller design for multivariable systems based on two degrees of freedom control scheme. Int J Control Autom Syst2018; 16: 689–701.
27.
PanL.Advanced control and online optimization technology and its application. Beijing: China Machine Press, 2009, pp.160–163.
28.
TruongNLVLeeM. Multi-loop PI/PID controller design based on direct synthesis for multivariable systems. Lect Notes Eng Comput Sci2008; 2173: 852–856.
29.
RoffelBBetlemBH.Internal model control. In: Advanced practical process control. Berlin: Springer, 2004, pp.161–169.
30.
IndranilPSaptarshiD.Fractional order controller tuning using swarm and evolutionary algorithms. In: Intelligent fractional order systems and control. Berlin: Springer, 2013, pp.87–131.
31.
ZhangGXJinWDLiN.An improved quantum genetic algorithm and its application. In: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 9th International Conference, RSFDGRC 2003, Chongqing, China, 26–29 May, 2003, pp.449–452. Berlin: Springer.
YuLShiFWangH, et al. Analysis of 30 cases of MATLAB intelligent algorithm. Beijing: Beijing University of Aeronautics and Astronautics Press, 2011, pp.77–87.
34.
ZhouCHQianF.Improvement of quantum genetic algorithm and its application. Comput Appl2008; 28: 286–288.
35.
AlekseiTEduardPJuriB. Gain and order scheduled fractional-order PID control of fluid level in a multi-tank system. In: International conference on fractional differentiation and its applications 2014, Catania, Italy, 23–25 June 2014, pp.1–6. New York: IEEE.
36.
AlekseiTEduardPJuriB, et al. Fractional-order controller design and digital implementation using FOMCON toolbox for MATLAB. In: 2013 IEEE conference on computer aided control system design (CACSD), Hyderabad, India, 28–30 August 2013, pp.340–345. New York: IEEE.
37.
XueDYZhaoCNChenYQ.Fractional order PID control of a DC-motor with elastic shaft: a case study. In: 2006 American Control Conference, Minneapolis, MN, 14–16 June 2006, pp.3182–3187. New York: IEEE.
38.
AlekseiTEduardPJuriB. FOMCON: Fractional-order modeling and control toolbox for MATLAB. In: Proceedings of the 18th international conference mixed design of integrated circuits and systems – MIXDES 2011, Gliwice, Poland, 16–18 June 2011, pp.684–689. New York: IEEE.
