Abstract
Unmanned ground vehicles (UGVs) play an increasingly important role in future space exploration and battlefield. This work is concerned with the automatic path tracking control of UGVs. By using the structure properties of the system, neuro-adaptive control algorithms are developed for high precision tracking without involving complex design procedures – the proposed control scheme only demands partial information of the system, no detail description of the system model is needed. Furthermore, uncertain effects such as external disturbance and uncertain parameters can easily be handled. In addition, all the internal signals are uniformly bounded and the control torque is smooth anywhere.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Elfes, A., Bueno, S.S., Bergerman, M., de Paiva, E.C., Ramos, J.G.: Robotic Airships for Exploration of Planetary Bodies with An Atmosphere. Autonomy Challenges, Auto Robots 14, 147–164 (2003)
Hirose, S., Kuwahara, H., Wakabayashi, Y., Yoshioka, N.: The Mobility Design Concepts/characteristics and Ground Testing of an Offset-wheel Rover Vehicle. Space Tech. 17, 183–193 (1997)
Ito, T., Jahan, M., Abadi, S.M.: Agent-based Material Handling and Inventory Planning in Warehouse. J. Intell. Manuf. 13, 201–210 (2002)
Letherwood, M.D., Gunter, D.D.: Ground Vehicle Modeling and Simulation of Military Vehicles Using High Performance Computing. Parallel Compute 27, 109–140 (2001)
Brockett, R.W.: Asymptotic Stability and Feedback Linearization in Differential Geometric Control Theory. Birkhauser, Cambridge (1983)
Rigatos, G.G., Tzafestas, C.S., Tzafestas, S.G.: Mobile Robot Motion Control in Partially Unknown Environments Using a Sliding Mode Fuzzy Logic Controller. Robotics and Autonomous Systems 2(2), 313–319 (1994)
Yang, M., Kim, J.H.: Sliding Mode Control for Trajectory Tracking of Nonholonomic Wheeled Mobile Robots. IEEE Trans. on Robotics and Automation 15(3), 578–587 (1999)
Fierro, R., Lewis, F.V.: Control of a Nonholonmic Mobile Robot: Backstepping Kinematics into Dynamics. J. Robotics Systems 14(3), 149–163 (1997)
Zhang, Q., Shippen, J., Jones, B.: Robost Backstepping and Neural Network Control of a Low Quality Nonlonomic Mobile Robot. Int. J. Mach. To. Manuf. 39(7), 1117–1134 (1999)
Bolzern, P., Desantis, R., Locatelli, M., Masciouscchi, A.D.: Path Tracking for Articulated Vehicles with Off-axle Hitching. IEEE Trans on Control System Tech. 6(4), 515–523 (1998)
Song, Y.D.: Adaptive Motion Tracking Control of Robot Manipulators-non-regressor Based Approach. Int. J. Control 63(1), 41–54 (1996)
Lewis, F.L., Yesildirek, A., Liu, K.: Multilayer Neural-net Robot Manipulators. MacMillan, New York (1993)
Sarkar, N., Yun, X., Kumar, V.: Control of Mechanical Systems with Rolling Constraints: Application to Dynamic Control of Mobile Robots. Int. J. Robot. Res. 13(1), 55–69 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liao, X., Sun, Z., Weng, L., Li, B., Song, Y., Li, Y. (2006). Adaptive Neural Network Path Tracking of Unmanned Ground Vehicle. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_179
Download citation
DOI: https://doi.org/10.1007/11760023_179
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
Online ISBN: 978-3-540-34438-4
eBook Packages: Computer ScienceComputer Science (R0)