Observer-based fault detection for robot manipulators

The adoption of efficient online fault detection and isolation (FDI) tools is becoming of the utmost importance for robots, especially for those operating in remote or hazardous environments, where a high degree of safety and self-diagnostics capabilities is required. In this paper a new observer-based approach to fault detection and isolation for robot manipulators is proposed. A nonlinear observer of the system's outputs, joint position and velocities, is designed directly in the discrete-time domain; in order to improve the robustness of the observer to unknown dynamics and discretization errors, a linear feedback of the observation error and a delayed nonlinear compensation action are added. The residuals for the detection of both sensor and actuator failures are then generated from the observation errors. Simulation results show the effectiveness of the proposed approach, even if a relatively low sampling rate is adopted and in the presence of large modeling errors.

[1]  A. Willsky,et al.  Analytical redundancy and the design of robust failure detection systems , 1984 .

[2]  Charles P. Neuman,et al.  Discrete dynamic robot models , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Graham Vahl Davis.  Numerical Methods in Engineering & Science , 1986 .

[4]  Peter D. Richardson,et al.  Numerical Methods in Engineering and Science , 1987 .

[5]  Kamal Youcef-Toumi,et al.  A Time Delay Controller for Systems with Unknown Dynamics , 1988, 1988 American Control Conference.

[6]  J.J. Gertler,et al.  Survey of model-based failure detection and isolation in complex plants , 1988, IEEE Control Systems Magazine.

[7]  Rolf Isermann.  Process fault diagnosis based on process model knowledge , 1988 .

[8]  Paul M. Frank,et al.  Dynamic Model Based Incipient Fault Detection Concept for Robots , 1990 .

[9]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..

[10]  R. Isermann,et al.  Process Fault Diagnosis Based on Process Model Knowledge: Part I—Principles for Fault Diagnosis With Parameter Estimation , 1991 .

[11]  Bernd Freyermuth.  An approach to model based fault diagnosis of industrial robots , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[12]  Wyatt S. Newman,et al.  Reflexive collision avoidance: a generalized approach , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[13]  Joseph R. Cavallaro,et al.  A dynamic fault tolerance framework for remote robots , 1995, IEEE Trans. Robotics Autom..

[14]  Anthony A. Maciejewski,et al.  A local measure of fault tolerance for kinematically redundant manipulators , 1996, IEEE Trans. Robotics Autom..

[15]  Paul M. Frank,et al.  Observer-based supervision and fault detection in robots using nonlinear and fuzzy logic residual evaluation , 1996, IEEE Trans. Control. Syst. Technol..