Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances

Citation

Caccauale, F. and Villani, L. (2004), "Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances", Industrial Robot, Vol. 31 No. 4, pp. 375-375. https://doi.org/10.1108/ir.2004.31.4.375.1

Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances provides extended versions of the lectures given at a workshop held in conjunction with the 2002 IEEE International Symposium on Intelligent Control held in Vancouver, Canada. The books presents six chapters that each address important theoretical and practical applications to assist in the design of systems with self‐diagnosis capabilities.

Chapter 1, Sliding Mode Observers and Their Application in Fault Diagnosis, reviews two commonly used approaches to sliding mode observer (SMO) design. It also addresses SMOs for linear and nonlinear systems, a simple sliding mode output observer for fault diagnosis, sliding mode functional observer (SMFO) based incipient fault diagnosis for nonlinear uncertain systems, and examples illustrating applications of SMOs for fault diagnosis for internal combustion engines, robots, and electric motors.

Chapter 2 discusses Fault Diagnosis and Fault Tolerant Control for Non‐Gaussian Stochastic Systems with Random Parameters, while chapter 3, Fault Diagnosis for Industrial Robots, compares different discrete‐time observer‐based approaches to fault diagnosis for mechanical manipulators. Topics addressed include: a simple model‐based fault diagnosis scheme; observer‐based fault diagnosis in the absence of velocity measurements; fault detection, isolation and identification; and experimental results.

The following two chapters present A Survey of Fault Detection/Tolerance Strategies for AUVs (Autonomous Underwater Vehicles) and ROVs (Remotely Operated Vehicles) and Failure Detection, Identification, and Reconfiguration in Flight Control. The final chapter of the book discusses Nonlinear Fault Detection of Hydraulic Systems, and focuses on nonlinear analytical redundancy – a model‐based state‐space technique that is theoretically guaranteed to derive the maximum number of independent tests of the consistency of sensor data with the system model and past control inputs.

Overall, this is a well‐written reference text, which is suitable for graduate students, researchers, and engineers who require an overview of some of the latest developments in fault diagnosis and fault tolerant control of mechatronic systems.