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Nonlinear Observer-Based Fault Detection and Isolation for a Manipulator Robot

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New Developments and Advances in Robot Control

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 175))

Abstract

Fault Detection and Isolation (FDI) techniques in robot manipulator is becoming one of the most phenomena in robotics in order to ensure higher levels of safety and productivity. Research, has been produced a considerable effort in seeking systematic approaches to fault detection for both linear and nonlinear dynamical systems. In the last decade considerable research efforts have been spent to seek for systematic approaches to Fault Detection (FD) in dynamical systems. Special attention has been addressing for robotic systems, especially for those operating in remote or hazardous environments, where a high degree of safety as well as self-detection capabilities are required. On the other hand, the development of effective strategies of fault detection for robot manipulators operating in an industrial context is a critical research task. Several FD techniques for robot manipulators have been proposed in the literature, although the problem of their application to industrial robots has not been extensively investigated.

In this chapter, we present a high-gain observer based fault detection and isolation scheme for a class of affine nonlinear systems. In order to test the effectiveness and the robustess of the proposed approach, a case study is developed for a special robot manipulator named Articulated Nimble Adaptable Trunk “ANAT” with a five-degree-of-freedom in order to detected and isolated sensor fault.

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References

  • Busawon, K., Farza, M., & Hammouri, H. (1998). Observer design for a special class of nonlinear systems. International Journal of Control, 71, 405–418.

    Article  MathSciNet  Google Scholar 

  • Craig, J. J. (1989). Introduction to robotics: Mechanics and control (2nd ed.). Boston: Addison-Wesley Longman Publishing, Inc.

    MATH  Google Scholar 

  • Dixon, E., Warren, W., Ian, D., Dawson, D. M., & Hartranft, J. P. (2000). Fault detection for robot manipulators with parametric uncertainty: A prediction-error-based approach. IEEE Transactions on Robotics and Automation, 16(6), 689–699.

    Article  Google Scholar 

  • Esfandiari, F., & Khalil, H. (1987). Observer-based design of uncertain systems: Recovering state feedback robustness under matching conditions. In Allerton Conference, Monticello (pp. 97–106).

    Google Scholar 

  • Farza, M., Hammouri, H., Jallut, C., & Lieto, J. (1999). State observation of a nonlinear system: Application to (bio) chemical processes. AICHE Journal, 45, 93–106.

    Article  Google Scholar 

  • Farza, M., M’Saad, M., & Rossignol, L. (2004). Observer design for a class of MIMO nonlinear systems. Automatica, 40, 135–143.

    Article  MathSciNet  Google Scholar 

  • Farza, M., M’saad, M., & Sekher, M. (2005). A set of observers for a class of nonlinear systems. In International Federation of Automation Control-IFAC’05, Prague, 37.

    Google Scholar 

  • Filaretov, V., Vukobratovic, M., & Zhirabok, A. (1999). Observer-based fault diagnosis in manipulation robots. Mechatronics, 9, 929–939.

    Article  Google Scholar 

  • Filaretov, V., Vukobratovic, M., & Zhirabok, A. (2003). Parity relation approach to fault diagnosis in manipulation robots. Mechatronics, 13, 141–152.

    Article  Google Scholar 

  • Frank, P. (1990). Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy? A survey and some new results. Automatica, 26, 459–474.

    Article  Google Scholar 

  • Frank, P. (1993). Advances in observer-based fault diagnosis. In TOOLDIAG’93, International Conference on Fault Diagnosis, Toulouse.

    Google Scholar 

  • Gauthier, J., & Kupka, I. (2001). Observability and observers for nonlinear systems. SIAM Journal Control Optimisation, 32, 181–188.

    Google Scholar 

  • Gauthier, J. P., Hammouri, H., & Othman, S. (1992). A simple observer for nonlinear systems – application to bioreactors. IEEE Transactions on Automatic Control, 37, 875–880.

    Article  MathSciNet  Google Scholar 

  • Gauthier, J. P., Hammouri, H., & Othman, S. (2001). A simple observer for nonlinear systems – application to bioreactors. IEEE Transactions on Automatic Control, 37, 875–880.

    Article  MathSciNet  Google Scholar 

  • Gertler, J. (1993). Residual generation in model-based fault diagnosis. Control Theory Advanced Technology, 9, 259–285.

    MathSciNet  Google Scholar 

  • Gertler, J., & Monajemy, R. (1995). The state of the art. Automatica, 31, 627–635.

    Article  Google Scholar 

  • Guernez, C., Cassar, J., & Staroswiecki, M. (1997). Process fault diagnosis based on modeling and estimation methods-a survey automatica. In IFAC Symposium SAFEPROCESS’97, Kingston upon Hull.

    Google Scholar 

  • Hammouri, H., & Farza, M. (2003). Nonlinear observers for locally uniformly observable systems. ESAIM, 9, 353–370.

    MathSciNet  MATH  Google Scholar 

  • Hammouri, H., Busawon, K., Yahoui, A., & Grellet, G. (2001). A nonlinear observer for induction motors. European Physical Journal-Applied Physics, 15, 181–188.

    Article  Google Scholar 

  • Hou, M., Busawon, K., & Saif, M. (2000). Observer design for a class of MIMO nonlinear systems. IEEE Transactions on Automatic Control, 45, 1350–1355.

    Article  MathSciNet  Google Scholar 

  • Isermann, R. (1984). Process fault diagnosis based on modeling and estimation methods-a survey automatica. International Federation of Automatic Control, 20, 387–404.

    MATH  Google Scholar 

  • Jollie, I. T. (2016). Simultaneous fault diagnosis for robot manipulators with actuator and sensor faults. Information Sciences, 366, 12–30.

    Article  MathSciNet  Google Scholar 

  • Khalil, H., & Praly, L. (2014). High-gain observers in nonlinear feedback control. International Journal of Robust and Nonlinear Control, 24, 993–1015.

    Article  MathSciNet  Google Scholar 

  • Khalil, H., & Saberi, A. (2007). Adaptive stabilization of a class on nonlinear systems using high-gain feedback. IEEE Transactions on Automatic Control, 32, 1031–1035.

    Article  MathSciNet  Google Scholar 

  • Koubaa, Y., Farza, M., & M’saad, M. (2004). Obsevateur adaptatif pour une classe des systèmes non linéaires. In 5th Conférence Internationale des Sciences et Techniques de l’Automatique, STA’04.

    Google Scholar 

  • Krishnaswami, V., & Rissoni, G. (1994). Nonlinear parity equation residual generation for fault detection and isolation. In IFAC Symposium SAFEPROCESS’94, Espoo (Vol. 1, pp. 317–322).

    Article  Google Scholar 

  • Ma, H. J., & Yang, G. H. (2016). Simultaneous fault diagnosis for robot manipulators with actuator and sensor faults. Information Sciences, 366, 12–30.

    Article  MathSciNet  Google Scholar 

  • Mironovsky, L. (1989). Functional diagnosis of nonlinear discrete-time processes. Autom Remote Control, 6, 150–157.

    MathSciNet  Google Scholar 

  • Nadri, M. (2001). Observation et commande des systèmes non linéaires et application aux bioprocédés. Thèse de doctorat, Université Claude Bernard Lyon-1.

    Google Scholar 

  • Patton, R. (1994). The state of the art. In IFAC Symposium SAFEPROCESS’94, Espoo (Vol. 1, pp. 1–24).

    Google Scholar 

  • Saberi, A., & Sannuti, P. (1990). Observer design for loop transfer recovery and for uncertain dynamical systems. IEEE Transactions on Automatic Control, 35, 878–897.

    Article  MathSciNet  Google Scholar 

  • Schneider, H., & Frank, P. M. (1996). Observed- based supervision and fault detection in robots using nonlinear and fuzzy logic residual evaluation. IEEE Transactions on Control Systems Technology, 4(3), 274–282.

    Article  Google Scholar 

  • Shim, H., Son, Y., & Seo, J. (2001). Semi-global observer for multi-output nonlinear systems. Systems and Control Letters, 42, 233–244.

    Article  MathSciNet  Google Scholar 

  • Shumsky, A. (1998). Parity relation method and its application to fault detection in nonlinear dynamic systems. Automation and Remote Control, 9, 155–165.

    Google Scholar 

  • Slotine, J. J., & Weiping, L. (1991). Applied nonlinear control. Englewood Cliffs: Printice-Hall International.

    MATH  Google Scholar 

  • Tornambe, A. (1988). Use of asymptotic observers having high gains in the state and parameter estimation. In 27th IEEE Conference on Decision and Control, Austin (pp. 1791–1794).

    Google Scholar 

  • Tornambe, A. (1992). High-gain observers for non-linear systems. International Journal of Systems Science, 23, 1475–1489.

    Article  MathSciNet  Google Scholar 

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Correspondence to Khaoula Oulidi Omali .

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Omali, K.O., Kabbaj, M.N., Benbrahim, M. (2019). Nonlinear Observer-Based Fault Detection and Isolation for a Manipulator Robot. In: Derbel, N., Ghommam, J., Zhu, Q. (eds) New Developments and Advances in Robot Control. Studies in Systems, Decision and Control, vol 175. Springer, Singapore. https://doi.org/10.1007/978-981-13-2212-9_7

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