Real-time predictive sliding mode control method for AGV with actuator delay

Zhi Chen , Jian Fu , Xiao-Wei Tu , Ao-Lei Yang , Min-Rui Fei

Advances in Manufacturing ›› 2019, Vol. 7 ›› Issue (4) : 448 -459.

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Advances in Manufacturing ›› 2019, Vol. 7 ›› Issue (4) : 448 -459. DOI: 10.1007/s40436-019-00275-0
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Real-time predictive sliding mode control method for AGV with actuator delay

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Abstract

In this paper, a predictive sliding mode control method based on multi-sensor fusion is proposed to solve the problem of insufficient accuracy in trajectory tracking caused by actuator delay. The controller, based on the kinematics model, uses an inner and outer two-layer structure to achieve decoupling of position control and heading control. A reference positional change rate is introduced into the design of controller, making the automatic guided vehicle (AGV) capable of real-time predictive control ability. A stability analysis and a proof of predictive sliding mode control theory are provided. The experimental results show that the new control algorithm can improve the performance of the AGV controller by referring to the positional change rate, thereby improving the AGV operation without derailing.

Keywords

Predictive sliding mode control / Multi-sensor fusion / Trajectory tracking / Real-time decoupling

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Zhi Chen, Jian Fu, Xiao-Wei Tu, Ao-Lei Yang, Min-Rui Fei. Real-time predictive sliding mode control method for AGV with actuator delay. Advances in Manufacturing, 2019, 7(4): 448-459 DOI:10.1007/s40436-019-00275-0

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References

[1]

Attia R, Orjuela R, Basset M. Combined longitudinal and lateral control for automated vehicle guidance. Veh Syst Dyn, 2014, 52(2): 261-279.

[2]

Katriniok A, Maschuw JP, Christen F et al (2013) Optimal vehicle dynamics control for combined longitudinal and lateral autonomous vehicle guidance. In: European control conference (ECC), 17–19 July, Zurich, Switzerland, pp 974–979

[3]

Watanabe K, Tang J, Nakamura M, et al. A fuzzy-Gaussian neural network and its application to mobile robot control. IEEE Trans Control Syst Technol, 2002, 4(2): 193-199.

[4]

Tang ZL, Ge SS, Tee KP, et al. Robust adaptive neural tracking control for a class of perturbed uncertain nonlinear systems with state constraints. IEEE Trans Syst Man Cybern Syst, 2017, 46(12): 1618-1629.

[5]

Fukao T, Nakagawa H, Adachi N. Adaptive tracking control of a nonholonomic mobile robot. IEEE Trans Robot Autom, 2000, 16(5): 609-615.

[6]

Guo L, Huang X, Ge P, et al. Lane changing trajectory tracking control for intelligent vehicle on curved road based on backstepping. J Jilin Univ (Eng and Technol Ed), 2013, 43(2): 323-328.

[7]

Rossetter EJ, Switkes JP, Gerdes JC. Experimental validation of the potential field lane keeping system. Int J Autom Technol, 2004, 5(2): 95-108.

[8]

Kritayakirana K, Gerdes JC. Autonomous vehicle control at the limits of handling. Int J Veh Auton Syst, 2012, 10(4): 271-296.

[9]

Falcone P, Borrelli F, Asgari J, et al. Predictive active steering control for autonomous vehicle systems. IEEE Trans Control Syst Technol, 2007, 15(3): 566-580.

[10]

Chwa D. Sliding-mode tracking control of nonholonomic wheeled mobile robots in Polar coordinates. IEEE Trans Control Syst Technol, 2004, 12(4): 637-644.

[11]

Cao Z, Zhao Y, Fu Y. Trajectory tracking control approach of a car-like mobile robot. Acta Electron Sin, 2012, 40(4): 632-635.

[12]

Yang JM, Kim JH. Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots. IEEE Trans Robot Autom, 1999, 15(3): 578-587.

[13]

Borrelli FI. MPC based approach to active steering for autonomous vehicle systems. Int J Veh Auton Syst, 2005, 3(2): 265-291.

[14]

Beal CE, Gerdes JC. Model predictive control for vehicle stabilization at the limits of handling. IEEE Trans Control Syst Technol, 2013, 21(4): 1258-1269.

[15]

Roselli F, Corno M, Savaresi SM et al (2017) H∞ control with look-ahead for lane keeping in autonomous vehicles. In: IEEE conference on control technology and applications, 27–30 August, Kohala Coast, USA, pp 2220–2225

[16]

Chen Z, Wang D, Zhen Z, et al. Take-off and landing control for a coaxial ducted fan unmanned helicopter. Airc Eng Aerosp Technol, 2017, 89(6): 764-776.

[17]

Fu J, Chen WH, Wu QX. Chattering-free sliding mode control with unidirectional auxiliary surfaces for miniature helicopters. Int J Intell Comput Cybern, 2012, 5(3): 421-438.

[18]

Chen Z, Wang D, Zhen Z. Modelling and hovering control for a coaxial unmanned helicopter using sliding mode. Aircr Eng Aerosp Technol, 2018, 90(5): 815-827.

[19]

Fu J, Wu QX, Mao ZH. Chattering-free SMC with unidirectional auxiliary surfaces for nonlinear system with state constraints. Int J Innov Comput Inf Control, 2013, 9(12): 4793-4809.

[20]

Feng Y, Yu X, Man Z. Non-singular terminal sliding mode control of rigid manipulators. Automatica, 2002, 38(12): 2159-2167.

[21]

Li THS, Chang SJ, Tong W. Fuzzy target tracking control of autonomous mobile robots by using infrared sensors. Fuzzy Syst IEEE Trans, 2004, 12(4): 491-501.

[22]

Bianco CGL, Piazzi A, Romano M. Smooth motion generation for unicycle mobile robots via dynamic path inversion. IEEE Trans Rob, 2004, 20(5): 884-891.

[23]

Samson C. Control of chained systems application to path following and time-varying point-stabilization of mobile robots. IEEE Trans Autom Control, 1995, 40(1): 64-77.

[24]

Yim H, Butler AC (1995) Motion planning using fuzzy logic control with minimum sensors. In: IEEE international symposium on intelligent control, 27–29 Aug, Monterey, CA, USA, pp 558–564

[25]

Mallem A, Nourredine S, Benaziza W (2016) Mobile robot trajectory tracking using PID fast terminal sliding mode inverse dynamic control. In: The 4th international conference on control engineering & information technology (CEIT), 12–18 December, Hammamet, Tunisia, pp 1–6

[26]

Do KD, Jiang ZP, Pan J. A global output-feedback controller for simultaneous tracking and stabilization of unicycle-type mobile robots. IEEE Trans Robot Autom, 2004, 20(3): 589-594.

[27]

Xiao S, Liu S, Jiang F, et al. Nonlinear dynamic response of reciprocating compressor system with rub-impact fault caused by subsidence. J Vib Control, 2019, 25(11): 1737-1751.

[28]

Huang SN, Ren W. Design of vehicle following control systems with actuator delays. Int J Syst Sci, 1997, 28(2): 145-151.

[29]

Xiao L, Darbha S, Gao F (2008) Stability of string of adaptive cruise control vehicles with parasitic delays and lags. In: The 11th international IEEE conference on intelligent transportation systems, 12–15 Oct, Beijing, China, pp 1101–1106

[30]

Choi SB, Hedrick JK. Robust throttle control of automotive engines: theory and experiment. J Dyn Syst Meas Contr, 1996, 118(1): 92.

[31]

Kahveci NE, Ioannou PA (2011) Automatic steering of vehicles subject to actuator saturation and delay. In: The 14th international IEEE conference on intelligent transportation systems, 5 October, Washington DC, USA, pp 119–124

[32]

Liu F, Chen Y (2017) Improved model predictive control for cooperative adaptive cruise control subject to actuator delay. In: 2017 Chinese automation congress (CAC), 20–22 October, Jinan, China, pp 4717–4722

Funding

Young Scientists Fund http://dx.doi.org/10.13039/501100010909(61603191)

Postdoctoral Research Foundation of China http://dx.doi.org/10.13039/501100010031(2018M630424)

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