Abstract
This paper investigates an algorithm for fault diagnosis in robot manipulators using a novel neural second-order sliding mode observer. Differently from the conventional neural network observer and first-order sliding mode observer for the robust fault estimation schemes, the second-order sliding mode observer is first designed and compared with them. Although the second-order sliding mode observer converges faster and with less error than each of the neural network and the first-order sliding mode observer does, it requires prior knowledge of the upper bound of the fault function. Because of this disadvantage, a neural second-order sliding mode observer is designed, which combines the second-order sliding mode observer with the neural network observer. The resulting observer not only preserves the features of the second-order sliding mode observer but also can improve it by removing the need for prior knowledge of the fault function upper bound. Computer simulation results for a PUMA560 industrial robot are also shown to verify the effectiveness of the proposed strategy.
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Abbreviations
- FD:
-
Fault diagnosis
- FDI:
-
Fault detection and isolation
- NN:
-
Neural network
- SM:
-
Sliding mode
- SOSM:
-
Second-order sliding mode
- NSOSM:
-
Neural second-order sliding mode
- EOI:
-
Equivalent Output Injection
References
Gertler, J. J., “Survey of model-based failure detection and isolation in complex plants,” Control Systems Magazine, Vol. 8, No. 6, pp. 3–11, 1988.
Frank, P. M. and Ding, X., “Survey of robust residual generation and evaluation methods in observer-based fault detection systems,” Journal of Process Control, Vol. 7, No. 6, pp. 403–424, 1997.
Polycarpou, M. M. and Helmicki, A. J., “Automated fault detection and accommodation: a learning systems approach,” IEEE Transactions on Systems, Man and Cybernetics, Vol. 25, No. 11, pp. 1447–1458, 1995.
Polycarpou, M. M. and Trunov, A. B., “Learning approach to nonlinear fault diagnosis: detectability analysis,” IEEE Transactions on Automatic Control, Vol. 45, No. 4, pp. 806–812, 2000.
Trunov, A. B. and Polycarpou, M. M., “Automated fault diagnosis in nonlinear multivariable systems using a learning methodology,” IEEE Transaction on Neural Networks, Vol. 11, No. 1, pp. 91–101, 2000.
Zhang, X., Parisini, T., and Polycarpou, M. M., “Sensor bias fault isolation in a class of nonlinear systems,” IEEE Transactions on Automatic Control, Vol. 50, No. 3, pp. 370–376, 2005.
Vemuri, A. T. and Polycarpou, M. M., “Neural-network-based robust fault diagnosis in robotic systems,” IEEE Transaction on Neural Networks, Vol. 8, No. 6, pp. 1410–1420, 1997.
Huang, S. N., Tan, K. K., and Lee, T. H., “Automated fault detection and diagnosis in mechanical systems,” IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, Vol. 37, No. 6, pp. 1094–6977, 2007.
Huang, S. N. and Kok, K. T., “Fault detection, isolation, and accommodation control in robotic systems,” IEEE Transaction on Automation Science and Engineering, Vol. 5, No. 3, pp. 480–489, 2008.
Eski, I., Erkaya, S., Savas, S., and Yildirim, S., “Fault detection on robot manipulators using artificial neural networks,” Robotics and Computer-Integrated Manufacturing, Vol. 27, No. 1, pp. 115–123, 2011.
Van, M., Kang, H.-J., and Ro, Y.-S., “A robust fault detection and isolation scheme for robot manipulators based on neural networks,” ICIC2011, LNCS 6838, pp. 25–32, Springer-Verlag, 2011.
Utkin, V., “Variable structure systems with sliding modes,” IEEE Transactions on Automatic Control, Vol. 22, No. 2, pp. 212–222, 1977.
Utkin, V., “Sliding modes in control and optimizations,” Springer-Verlag, Berlin, Germany, 1992.
Yun, D., Kim, H., and Boo, K., “Brake performance evaluation of ABS with sliding mode controller on a split road with driver model,” Int. J. Precis. Eng. Manuf., Vol. 12, No. 1, pp. 31–38, 2011.
Dinh, V.-T., Nguyen, H., Shin, S.-M., Kim, H.-K., Kim, S.-B., and Byun, G.-S., “Tracking control of omnidirectional mobile platform with disturbance using differential sliding mode controller,” Int. J. Precis. Eng. Manuf., Vol. 13, No.1, pp. 39–48, 2012.
Yi, X. and Saif, M., “Sliding mode observer for nonlinear uncertain systems,” IEEE Transactions on Automatic Control, Vol. 46, No. 12, pp. 2012–2017, 2001.
Veluvolu, K. C., Soh, Y. C., and Cao, W., “Robust observer with sliding mode estimation for nonlinear uncertain systems,” IET Control Theory & Applications, Vol. 1, No. 5, pp. 1533–1540, 2007.
Edwards, C., Spurgeon, S. K., and Patton, R. J., “Sliding mode observers for fault detection and isolation,” Automatica, Vol. 36, No. 4, pp. 541–553, 2000.
Levant., A., “Sliding order and sliding accuracy in sliding mode control,” International Journal of Control, Vol. 58, No. 6, pp. 1247–1263, 1993.
Levant, A., “Robust exact differentiation via sliding mode technique,” Automatica, Vol. 34, No. 3, pp. 379–384, 1998.
Bartolini, G., Ferrara, A., and Usai, E., “Chattering avoidance by second order sliding mode control,” IEEE Transactions on Automatic Control, Vol. 43, No. 2, pp. 241–246, 1998.
Brambilla, D., Capisani, L. M., Ferrara, A., and Pisu, P., “Fault Detection for Robot Manipulators via Second-Order Sliding Modes,” IEEE Transactions on Industrial Electronics, Vol. 55, No. 11, pp. 3954–3963, 2008.
Davila, J., Fridman, L., and Levant, A., “Second-order sliding-mode observer for mechanical systems,” IEEE Transactions on Automatic Control, Vol. 50, No. 11, pp. 1785–1789, 2005.
Davila, J., Fridman, L., and Poznyak, A., “Observation and Identification of Mechanical Systems via Second Order Sliding Modes,” International Workshop on Variable Structure Systems, pp. 232–237, 2006.
Edwards, C., Fridman, L., and Thein, M.-W. L., “Fault Reconstruction in a Leader/Follower Spacecraft System Using Higher Order Sliding Mode Observers,” Proceeding of American Control Conference, pp. 408–413, 2007.
Capisani, L. M., Ferrara, A., and Fridman, L., “Higher Order Sliding Mode observers for actuator faults Diagnosis in robot manipulators,” IEEE International Symposium on Industrial Electronics (ISIE), pp. 2103–2108, 2010.
Abdollahi, F., Talebi, H. A., and Patel, R. V., “A stable neural network-based observer with application to flexible-joint manipulators,” IEEE Transactions on Neural Networks, Vol. 17, No. 1, pp. 118–129, 2006.
Qing, W. and Saif, M., “A neural-fuzzy sliding mode observer for robust fault diagnosis,” Proceeding of American Control Conference, pp. 4982–4987, 2009.
Moreno, J. A. and Osorio, M., “A Lyapunov approach to secondorder sliding mode controllers and observers,” Proceeding of 47th IEEE Conference on Decision and Control, pp. 2856–2861, 2008.
Khalil, H., “Nonlinear systems,” Prentice Hall, New Jersey, USA, 2002.
Armstrong, B., Oussama, K., and Burdick, J., “The Explicit Dynamic Model and Inertial Parameters of the PUMA 560 Arm,” Proceeding of 1986 IEEE International Conference on Robotics and Automation, Vol. 3, pp. 510–518, 1986.
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Van, M., Kang, HJ. & Suh, YS. A novel neural second-order sliding mode observer for robust fault diagnosis in robot manipulators. Int. J. Precis. Eng. Manuf. 14, 397–406 (2013). https://doi.org/10.1007/s12541-013-0055-5
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DOI: https://doi.org/10.1007/s12541-013-0055-5