Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect

Ming Yue; Linjiu Wang; Teng Ma

doi:10.1109/JAS.2017.7510553

Volume 4 Issue 3

Jul. 2017

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

CiteScore: 23.5, Top 2% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2017 > 4(3): 498-506

Ming Yue, Linjiu Wang and Teng Ma, "Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect," IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 498-506, July 2017. doi: 10.1109/JAS.2017.7510553

Citation:

Ming Yue, Linjiu Wang and Teng Ma, "Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect," IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 498-506, July 2017. doi: 10.1109/JAS.2017.7510553

Citation:

PDF( 698 KB)

Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect

doi: 10.1109/JAS.2017.7510553

Ming Yue^{1
,
,},
Linjiu Wang^2
,,
Teng Ma^1
,

1.
School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China
2.
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China

Funds:

the National Natural Science Foundation of China 61573078

the National Natural Science Foundation of China 61573147

the International S & T Cooperation Program of China 2014DFB70120

the State Key Laboratory of Robotics and System SKL RS2015ZD06

More Information

Abstract

Abstract

Wheeled mobile robots (WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly. To overcome this drawback, this article presents a neural network (NN) based terminal sliding mode control (TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance. In contrast to the existing friction models, the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously. Besides, the presented control approach can combine the merits of both TSMC and radial basis function (RBF) neural networks techniques, thereby providing numerous excellent performances for the closed-loop system, such as finite time convergence and faster friction estimation property. Simulation results validate the proposed friction model and robustness of controller; these research results will improve the autonomy and intelligence of WMRs, particularly when the mobile platform suffers from the sophisticated unstructured environment.
- Ground friction,
- radial basis function (RBF) neural network (NN),
- slippage effect,
- terminal sliding mode control (TSMC),
- wheeled mobile robot (WMR)

FullText(HTML)

References(39)

References

[1]	Z. P. Jiang and H. Nijmeijer, "Tracking control of mobile robots: a case study in backstepping, " Automatica, vol. 33, no. 7, pp. 1393-1399, Jul. 1997. https://www.researchgate.net/publication/220158566_Tracking_Control_of_Mobile_Robots_A_Case_Study_in_Backstepping
[2]	W. E. Dixon, A. Behal, D. M. Dawson, and S. P. Nagarkatti, Nonlinear Control of Engineering Systems:A Lyapunov-Based Approach. Boston, USA:Springer, 2003.
[3]	K. D. Do, "Bounded controllers for global path tracking control of unicycle-type mobile robots, " Robot. Autonom. Syst. , vol. 61, no. 8, pp. 775-784, Aug. 2013. http://www.sciencedirect.com/science/article/pii/S0921889013000766
[4]	J. S. Huang, C. Y. Wen, W. Wang, and Z. P. Jiang, "Adaptive output feedback tracking control of a nonholonomic mobile robot, " Automatica, vol. 50, no. 3, pp. 821-831, Mar. 2014. http://www.sciencedirect.com/science/article/pii/S0005109813005955
[5]	X. B. Zhang, Y. C. Fang, and N. Sun, "Visual servoing of mobile robots for posture stabilization: from theory to experiments, " Int. J. Robust Nonlinear Control, vol. 25, no. 1, pp. 1-15, Jan. 2015. doi: 10.1002/rnc.3067/full
[6]	C. G. Yang, Z. J. Li, R. X. Cui, and B. G. Xu, "Neural network-based motion control of an underactuated wheeled inverted pendulum model, " IEEE Trans. Neural Netw. Learn. Syst. , vol. 25, no. 11, pp. 2004-2016, Nov. 2014. http://ieeexplore.ieee.org/abstract/document/6762995/
[7]	J. J. Sun and Z. J. Li, "Development and implementation of a wheeled inverted pendulum vehicle using adaptive neural control with extreme learning machines, " Cogn. Comput. , vol. 7, no. 6, pp. 740-752, Dec. 2015. http://www.eng.yale.edu/grablab/pubs/vasudevan_jmr2015.pdf
[8]	M. Yue, C. An, Y. Du, and J. Z. Sun, "Indirect adaptive fuzzy control for a nonholonomic/underactuated wheeled inverted pendulum vehicle based on a data-driven trajectory planner, " Fuzzy Sets Syst. , vol. 290, pp. 158-177, May 2016. https://www.semanticscholar.org/paper/Indirect-adaptive-fuzzy-control-for-a-nonholonomic-Yue-An/030b2599f4c8ea2669c0158e152ad0e7a42f864c
[9]	K. Iagnemma, S. Kang, H. Shibly, and S. Dubowsky, "Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers, " IEEE Trans. Robot. , vol. 20, no. 5, pp. 921-927, Oct. 2004. http://dl.acm.org/citation.cfm?id=2211698
[10]	L. Ding, Z. Q. Deng, H. B. Gao, J. G. Tao, K. D. Iagnemma, and G. J. Liu, "Interaction mechanics model for rigid driving wheels of planetary rovers moving on sandy terrain with consideration of multiple physical effects, " J. Field Robot. , vol. 32, no. 6, pp. 827-859, Sep. 2015. doi: 10.1002/rob.21533/abstract
[11]	Y. Okada, K. Nagatani, K. Yoshida, S. Tadokoro, T. Yoshida, and E. Koyanagi, "Shared autonomy system for tracked vehicles on rough terrain based on continuous three-dimensional terrain scanning, " J. Field Robot. , vol. 28, no. 6, pp. 875-893, Nov. -Dec. 2011. https://www.researchgate.net/profile/Kazuya_Yoshida3/publication/220647967_Shared_Autonomy_System_for_Tracked_Vehicles_on_Rough_Terrain_Based_on_Continuous_Three-Dimensional_Terrain_Scanning/links/564f714b08ae4988a7a83da7.pdf?origin=publication_list
[12]	L. Ding, H. B. Gao, Z. Q. Deng, K. Nagatani, and K. Yoshida, "Experimental study and analysis on driving wheels' performance for planetary exploration rovers moving in deformable soil, " J. Terramech. , vol. 48, no. 1, pp. 27-45, Feb. 2011. https://www.researchgate.net/publication/223349856_Experimental_study_and_analysis_on_driving_wheels%27_performance_for_planetary_exploration_rovers_moving_in_deformable_soil
[13]	C. Canudas-de-Wit, P. Tsiotras, E. Velenis, M. Basset, and G. Gissinger, "Dynamic friction models for road/tire longitudinal interaction, " Vehicle Syst. Dyn. , vol. 39, no. 3, pp. 189-226, Mar. 2003. http://dcsl.gatech.edu/papers/iasted02b.pdf
[14]	C. Canudas-de-Wit, H. Olsson, K. J. Astrom, and P. Lischinsky, "A new model for control of systems with friction, " IEEE Trans. Autom. Control, vol. 40, no. 3, pp. 419-425, Mar. 1995. doi: 10.1177/0959651812441749
[15]	H. B. Pacejka and E. Bakker, "The magic formula tyre model, " Vehicle Syst. Dyn. , vol. 21, no. S1, pp. 1-18, Jan. 1992. doi: 10.1080/00423119208969994
[16]	Y. C. Fang, B. J. Ma, P. C. Wang, and X. B. Zhang, "A motion planningbased adaptive control method for an underactuated crane system, " IEEE Trans. Control Syst. Technol. , vol. 20, no. 1, pp. 241-248, Jan. 2012.
[17]	L. Lu, B. Yao, Q. F. Wang, and Z. Chen, "Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model, " Automatica, vol. 45, no. 12, pp. 2890-2896, Dec. 2009. https://www.researchgate.net/profile/Bin_Yao2/publication/3414835_Adaptive_robust_precision_motion_control_of_linear_motors_with_negligible_electrical_dynamics_Theory_and_experiments/links/0fcfd50b988462d124000000.pdf
[18]	N. Sun, Y. C. Fang, and H. Chen, "A new antiswing control method for underactuated cranes with unmodeled uncertainties: theoretical design and hardware experiments, " IEEE Trans. Ind. Electron. , vol. 62, no. 1, pp. 453-465, Jan. 2015. https://www.researchgate.net/profile/Ning_Sun12/publication/309573652_2015_TIE_A_New_Antiswing_Control_Method_for_Underactuated_Craneswith_Unmodeled_Uncertainties_Theoretical_Design_andHardware_Experiments/links/581808fa08aeb720f689b88d.pdf?origin=publication_list
[19]	R. R. Wang and J. M. Wang, "Tire-road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation, " Control Eng. Pract. , vol. 21, no. 1, pp. 65-75, Jan. 2013. https://www.researchgate.net/publication/222300981_Estimation_of_vehicle_sideslip_tire_force_and_wheel_cornering_stiffness
[20]	H. B. Gao, X. G. Song, L. Ding, K. R. Xia, N. Li, and Z. Q. Deng, "Adaptive motion control of wheeled mobile robot with unknown slippage, " Int. J. Control, vol. 87, no. 8, pp. 1513-1522, Mar. 2014. https://www.researchgate.net/profile/Xingguo_Song/publication/262582257_Adaptive_motion_control_of_wheeled_mobile_robot_with_unknown_slippage/links/568c728d08ae197e4268c2aa.pdf?origin=publication_list
[21]	Z. J. Li, S. M. Deng, C. Y. Su, G. L. Li, Z. G. Yu, Y. J. Liu, and M. Wang, "Decentralised adaptive control of cooperating robotic manipulators with disturbance observers, " IET Control Theory Appl. , vol. 8, no. 7, pp. 515-521, May 2014. https://www.researchgate.net/publication/262231731_Decentralised_adaptive_control_of_cooperating_Robotic_manipulators_with_disturbance_observers
[22]	Z. J. Li, Y. P. Yang, and J. X. Li, "Adaptive motion/force control of mobile under-actuated manipulators with dynamics uncertainties by dynamic coupling and output feedback, " IEEE Trans. Control Syst. Technol. , vol. 18, no. 5, pp. 1068-1079, Sep. 2010. https://www.researchgate.net/publication/224606423_Adaptive_MotionForce_Control_of_Mobile_Under-Actuated_Manipulators_With_Dynamics_Uncertainties_by_Dynamic_Coupling_and_Output_Feedback
[23]	N. Sun, Y. C. Fang, H. Chen, and B. He, "Adaptive nonlinear crane control with load hoisting/lowering and unknown parameters: design and experiments, " IEEE/ASME Trans. Mechatron. , vol. 20, no. 5, pp. 2107-2119, Oct. 2015.
[24]	N. Sun, Y. C. Fang, and X. B. Zhang, "Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs, " Automatica, vol. 49, no. 5, pp. 1318-1325, May 2013. http://www.sciencedirect.com/science/article/pii/S000510981300040X
[25]	Z. J. Li, Y. N. Zhang, and Y. P. Yang, "Support vector machine optimal control for mobile wheeled inverted pendulums with unmodelled dynamics, " Neurocomputing, vol. 73, no. 13-15, pp. 2773-2782, Aug. 2010. http://www.sciencedirect.com/science/article/pii/S0925231210002067
[26]	J. A. Rossiter, Model-Based Predictive Control: A Practical Approach. Boca Raton, FL, USA: CRC Press, 2003.
[27]	L. X. Zhang, S. L. Zhuang, and R. D. Braatz, "Switched model predictive control of switched linear systems: feasibility, stability and robustness, " Automatica, vol. 67, pp. 8-21, May 2016. http://www.sciencedirect.com/science/article/pii/S000510981600011X
[28]	Y. J. Liu, S. C. Tong, and C. L. P. Chen, "Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeled dynamics, " IEEE Trans. Fuzzy Syst. , vol. 21, no. 2, pp. 275-288, Apr. 2013. http://www.sciencedirect.com/science/article/pii/S000510981400449X
[29]	Y. M. Li, S. C. Tong, and T. S. Li, "Observer-based adaptive fuzzy tracking control of MIMO stochastic nonlinear systems with unknown control directions and unknown dead zones, " IEEE Trans. Fuzzy Syst. , vol. 23, no. 4, pp. 1228-1241, Aug. 2015. https://www.semanticscholar.org/paper/Adaptive-Neural-Network-Tracking-Control-of-MIMO-Zhang-Ge/7f96ac9aca570ada6da7eff1798b6fd93250359c
[30]	W. He, S. S. Ge, Y. N. Li, E. Chew, and Y. S. Ng, "Neural network control of a rehabilitation robot by state and output feedback, " J. Intell. Robot. Syst. , vol. 80, no. 1, pp. 15-31, Oct. 2015. http://dl.acm.org/citation.cfm?id=2821996
[31]	Y. J. Liu and S. C. Tong, "Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input, " IEEE Trans. Cybern. , vol. 45, no. 3, pp. 497-505, Mar. 2015.
[32]	Q. L. Hu, B. Li, and A. H. Zhang, "Robust finite-time control allocation in spacecraft attitude stabilization under actuator misalignment, " Nonlinear Dyn. , vol. 73, no. 1-2, pp. 53-71, Jul. 2013. https://www.researchgate.net/publication/257634090_Robust_finite-time_control_allocation_in_spacecraft_attitude_stabilization_under_actuator_misalignment
[33]	Q. L. Hu, B. Y. Jiang, and M. I. Friswell, "Robust saturated finite time output feedback attitude stabilization for rigid spacecraft, " J. Guid. Control Dyn. , vol. 37, no. 6, pp. 1914-1929, 2014. https://www.researchgate.net/publication/269785527_Robust_Saturated_Finite_Time_Output_Feedback_Attitude_Stabilization_for_Rigid_Spacecraft
[34]	Q. L. Hu and J. Zhang, "Relative position finite-time coordinated tracking control of spacecraft formation without velocity measurements, " ISA Trans. , vol. 54, pp. 60-74, Jan. 2015. https://www.researchgate.net/profile/Jian_Zhang252/publication/265090411_Relative_position_finite-time_coordinated_tracking_control_of_spacecraft_formation_without_velocity_measurements/links/579d52a208ae80bf6ea487ae.pdf?origin=publication_detail
[35]	S. H. Li, M. M. Zhou, and X. H. Yu, "Design and implementation of terminal sliding mode control method for PMSM speed regulation system, " IEEE Trans. Ind. Inf. , vol. 9, no. 4, pp. 1879-1891, Nov. 2013. https://www.researchgate.net/publication/260626819_Design_and_Implementation_of_Terminal_Sliding_Mode_Control_Method_for_PMSM_Speed_Regulation_System
[36]	J. X. Wang, S. H. Li, J. Yang, B. Wu, and Q. Li, "Extended state observer-based sliding mode control for PWM-based DC-DC buck power converter systems with mismatched disturbances, " IET Control Theory Appl. , vol. 9, no. 4, pp. 579-586, Feb. 2015. https://www.researchgate.net/publication/273287139_Extended_state_observer-based_sliding_mode_control_for_PWM-based_DC-DC_buck_power_converter_systems_with_mismatched_disturbances
[37]	M. Yue, S. Wang, and Y. S. Zhang, "Adaptive fuzzy logic-based sliding mode control for a nonholonomic mobile robot in the presence of dynamic uncertainties, " Proc. Instit. Mech. Eng. C J. Mech. Eng. Sci. , vol. 229, no. 11, pp. 1979-1988, Sep. 2015. https://www.researchgate.net/profile/Jafar_Keighobadi/publication/266892796_Dynamic_Sliding_Mode_Controller_for_Trajectory_Tracking_Of_Nonholonomic_Mobile_Robots/links/564aef7c08ae44e7a28e4534.pdf?inViewer=0&pdfJsDownload=0&origin=publication_detail
[38]	S. S. Ge, C. C. Hang, T. H. Lee, and T. Zhang, Stable Adaptive Neural Network Control. New York, USA:Springer, 2002.
[39]	W. S. Chen, L. C. Jiao, and J. S. Wu, "Globally stable adaptive robust tracking control using RBF neural networks as feedforward compensators," Neural Comput. Appl., vol. 21, no. 2, pp. 351-363, Mar. 2012. http://dl.acm.org/citation.cfm?id=2157566

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(9)

Get Citation

PDF

XML

Article Metrics

Article views (1222) PDF downloads(127)

Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect

doi: 10.1109/JAS.2017.7510553

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Export File

Citation

Format

Content