Bibliothèque de L'IMIST/CNRST

Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing huma.

Includes bibliographical references (p. [351]-375) and index.

1. Industrial robots in contact-free operation -- 2. Industrial robots in compliance tasks -- 3. Mobile robots and autonomous vehicles -- 4. Adaptive control methods for industrial systems -- 5. Robust control methods for industrial systems -- 6. Filtering and estimation methods for industrial systems -- 7. Sensor fusion-based control for industrial systems -- 8. Distributed filtering and estimation for industrial systems -- 9. Fault detection and isolation for industrial systems -- 10. Application of fault diagnosis to industrial systems -- 11. Optimization methods for motion planning of multi-robot systems -- 12. Optimization methods for target tracking by multi-robot systems -- 13. Optimization methods for industrial automation -- 14. Machine learning methods for industrial systems control -- 15. Machine learning methods for industrial systems fault diagnosis -- 16. Applications of mahcine vision to industrial systems.