×

Adaptive robust quadratic stabilization tracking control for robotic system with uncertainties and external disturbances. (English) Zbl 1291.93280

Summary: An adaptive robust quadratic stabilization tracking controller with hybrid scheme is proposed for robotic system with uncertainties and external disturbances. The hybrid scheme combines Computed Torque Controller (CTC) with an adaptive robust compensator, in which Variable Structure Control (VSC) and \(H_{\infty}\) optimal control approaches are adopted. The uncertain robot manipulator is mainly controlled by CTC, the VSC is used to eliminate the effect of the uncertainties and ensure global stability, and \(H_{\infty}\) approach is designed to achieve a certain tracking performance of closed-loop system. A quadratic stability approach, which allows separate treatment of parametric uncertainties, is used to reduce the conservatism of the conventional robust control approach. It can be also guaranteed that all signals in closed-loop system are bounded. The validity of the proposed control scheme is shown by computer simulation of a two-link robotic manipulator.

MSC:

93D21 Adaptive or robust stabilization
93C85 Automated systems (robots, etc.) in control theory
93C73 Perturbations in control/observation systems
93B12 Variable structure systems
93B36 \(H^\infty\)-control

References:

[1] Book, W. J., Modeling, design, and control of flexible manipulator arms: a tutorial review, Proceedings of the 29th IEEE Conference on Decision and Control, IEEE Press
[2] Lewis, F. L.; Jagannathan, S.; Yesildirek, A., Neural Network Control of Robot Manipulators and Nonlinear Systems (2002), SIAM Press: Philadelphia, Pa, USA, SIAM Press
[3] Luh, J. Y. S., Conventional controller design for industrial robots—a tutorial, IEEE Transactions on Systems, Man and Cybernetics, 13, 3, 298-316 (1983) · Zbl 0509.94001 · doi:10.1109/TSMC.1983.6313163
[4] Middleton, R. H.; Goodwin, G. C., Adaptive computed torque control for rigid link manipulations, Systems & Control Letters, 10, 1, 9-16 (1988) · Zbl 0636.93051 · doi:10.1016/0167-6911(88)90033-3
[5] Song, Z.; Yi, J.; Zhao, D.; Li, X., A computed torque controller for uncertain robotic manipulator systems: fuzzy approach, Fuzzy Sets and Systems, 154, 2, 208-226 (2005) · Zbl 1068.93046 · doi:10.1016/j.fss.2005.03.007
[6] Zuo, Y.; Wang, Y.; Liu, X.; Yang, S. X.; Huang, L.; Wu, X.; Wang, Z., Neural network robust \(H_\infty\) tracking control strategy for robot manipulators, Applied Mathematical Modelling, 34, 7, 1823-1838 (2010) · Zbl 1193.93094 · doi:10.1016/j.apm.2009.09.026
[7] Ortega, R.; Spong, M. W., Adaptive motion control of rigid robots: a tutorial, Automatica, 25, 6, 877-888 (1989) · Zbl 0695.93064
[8] Battilotti, S.; Lanari, L., Adaptive disturbance attenuation with global stability for rigid and elastic joint robots, Automatica, 33, 2, 239-243 (1997) · Zbl 0963.93063
[9] Kaynak, O.; Erbatur, K.; Ertugrul, M., The fusion of computationally intelligent methodologies and sliding-mode control—a survey, IEEE Transactions on Industrial Electronics, 48, 1, 4-17 (2001) · doi:10.1109/41.904539
[10] Yeung, K. S.; Chen, Y. P., A new controller design for manipulators using the theory of variable structure systems, IEEE Transactions on Automatic Control, 33, 2, 200-206 (1988) · Zbl 0633.93026 · doi:10.1109/9.391
[11] Lin, S.; Goldenberg, A. A., Robust damping control of mobile manipulators, IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics, 32, 1, 126-132 (2002) · doi:10.1109/3477.979968
[12] Alonge, F.; d’Ippolito, F.; Raimondi, F. M., Globally convergent adaptive and robust control of robotic manipulators for trajectory tracking, Control Engineering Practice, 12, 9, 1091-1100 (2004) · doi:10.1016/j.conengprac.2003.11.007
[13] Wang, Y.; Peng, J.; Sun, W.; Yu, H.; Zhang, H., Robust adaptive tracking control of robotic systems with uncertainties, Journal of Control Theory and Applications, 6, 3, 281-286 (2008) · doi:10.1007/s11768-008-6147-6
[14] Rubio, J. J.; Zamudio, Z.; Pacheco, J.; Vargas, D. M., Proportional derivative control with inverse dead-zone for pendulum systems, Mathematical Problems in Engineering, 2013 (2013) · Zbl 1296.93126 · doi:10.1155/2013/173051
[15] Torres, C.; Rubio, J. J.; Aguilar-Ibáñez, C.; Pérez-Cruz, J. H., Stable optimal control applied to a cylindrical robotic arm, Neural Computing and Applications, 24, 3-4, 937-944 (2014) · doi:10.1007/s00521-012-1294-6
[16] Galvan, S.; Moreno-Armendariz, M. A.; Rubio, J. J.; Rodriguez, F. I.; Yu, W.; Ibáñez, C. F. A., Dual PD control regulation with nonlinear compensation for a ball and plate system · Zbl 1407.93251
[17] Hsu, Y. C.; Chen, G.; Li, H. X., A fuzzy adaptive variable structure controller with applications to robot manipulators, IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics, 31, 3, 331-340 (2001) · doi:10.1109/3477.931517
[18] Hu, H.; Woo, P.-Y., Fuzzy supervisory sliding-mode and neural-network control for robotic manipulators, IEEE Transactions on Industrial Electronics, 53, 3, 929-940 (2006) · doi:10.1109/TIE.2006.874261
[19] Sun, F. C.; Sun, Z. Q.; Feng, G., An adaptive fuzzy controller based on sliding mode for robot manipulators, IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics, 29, 5, 661-667 (1999) · doi:10.1109/3477.790451
[20] Lewis, F. L.; Liu, K.; Yesildirek, A., Neural net robot controller with guaranteed tracking performance, IEEE Transactions on Neural Networks, 6, 3, 703-715 (1995) · doi:10.1109/72.377975
[21] Liu, Z.; Li, C., Fuzzy neural networks quadratic stabilization output feedback control for biped robots via \(H_\infty\) approach, IEEE Transactions on Systems, Man, and Cybernetics B: Cybernetics, 33, 1, 67-84 (2003) · doi:10.1109/TSMCB.2003.808177
[22] Peng, J.; Wang, J.; Wang, Y., Neural network based robust hybrid control for robotic system: an \(H_\infty\) approach, Nonlinear Dynamics, 65, 4, 421-431 (2011) · Zbl 1280.93058 · doi:10.1007/s11071-010-9902-4
[23] Sun, F.; Sun, Z.; Woo, P.-Y., Neural network-based adaptive controller design of robotic manipulators with an observer, IEEE Transactions on Neural Networks, 12, 1, 54-67 (2001) · doi:10.1109/72.896796
[24] Rubio, J. J., Modified optimal control with a backpropagation network for robotic arms, IET Control Theory & Applications, 6, 14, 2216-2225 (2012) · doi:10.1049/iet-cta.2011.0322
[25] Chang, Y. C., Neural network-based \(H_\infty\) tracking control for robotic systems, IEE Proceedings—Control Theory and Applications, 147, 3, 303-311 (2000) · doi:10.1049/ip-cta:20000257
[26] Wai, R.-J., Tracking control based on neural network strategy for robot manipulator, Neurocomputing, 51, 425-445 (2003) · doi:10.1016/S0925-2312(02)00626-4
[27] Slotine, J. J. E.; Li, W., Applied Nonlinear Control (1991), Englewood Cliffs, NJ, USA: Prentice-Hall, Englewood Cliffs, NJ, USA · Zbl 0753.93036
[28] Aguilar-Ibáñez, C.; Mendoza-Mendoza, J. A.; Suarez-Castañon, M.; Davila, J., A nonlinear robust PI controller for an uncertain system, International Journal of Control (2014) · Zbl 1291.93103 · doi:10.1080/00207179.2013.868606
[29] Rubio, J. J.; Gutierrez, G.; Pacheco, J.; Pérez-Cruz, H., Comparison of three proposed controls to accelerate the growth of the crop, International Journal of Innovative Computing, Information and Control, 7, 7, 4097-4114 (2011)
[30] Rubio, J. J.; Soriano, L. A.; Yu, W., Dynamic model of a wind turbine for the electric energy generation, Mathematical Problems in Engineering, 2014 (2014) · doi:10.1155/2014/409268
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.