Condition Monitoring And Dynamic Control Systems For Industrial Automation A Hands On Guide To Model Predictive Control MPC And Uncertainty Observers With Real World Applications And Research
✔️ Single-copy edition, 227 pages, 2017 release, English
This book is a practical guide for engineers and researchers exploring Model Predictive Control (MPC) and uncertainty observers in industrial automation. It highlights real-world applications such as condition monitoring for critical rotating and structural components in tidal turbines, and discusses digital manufacturing concepts aligned with Industry 4.0.
✅ Comprehensive coverage of Model Predictive Control (MPC) and uncertainty observers
✅ Real-world case studies including condition monitoring for turbines and heavy equipment
✅ Integrated monitoring system for fault detection and life-cycle prognosis
✅ Oil condition sensor concepts for wear debris and lubricant properties
✅ Industry 4.0 and digital manufacturing trends in modern automation
💡 What is a practical starting point for applying Model Predictive Control (MPC) in industrial automation? This long-tail question is commonly searched by engineers and managers aiming to optimize processes. - Model setup and data requirements for MPC in manufacturing environments - Uncertainty observer integration to handle nonlinear dynamics - Fault detection and condition monitoring for critical components - Implementation tips for stable, real-time control