Advanced Control Methods for Industrial Processes
Patricio Ordaz, Omar Jacobo Santos Sánchez, Liliam Rodríguez Guerrero, et al.
Naturwissenschaften, Medizin, Informatik, Technik / Chemie
Beschreibung
A detailed introduction to mathematical models for new and established control engineers
Control engineering is a system that helps us understand electrical, physical, chemical, and biochemical systems through the use of mathematical modeling, using inputs, outputs, and simulations. These experimental platforms are implemented in most systems of modern advanced control engineering.
Advanced Control Methods for Industrial Processes provides a solid grounding in traditional control techniques. It emphasizes practical application methods alongside the underlying theory and core instrumentation. Each chapter discusses the full profile of the technology covered, from the field layer and control layer to its implementation. It also includes the interfaces for advanced control systems: between controllers and systems theory, between different layers, and between operators-systems. Through an emphasis on the practical issues of components, devices, and hardware circuits, the book offers working principles and operation mechanisms that allow an engineer to put theory into practice for the advanced control techniques.
Advanced Control Methods for Industrial Processes readers will also find:
- A practical overview on advanced control methods applied to real-time and in-silico systems
- Specific parameters, install procedures, calibration and configuration methodologies necessary to conduct the relevant models
- Clear insights into the necessary mathematical models
- Tutorial material to facilitate the understanding of core concepts
Advanced Control Methods for Industrial Processes is an ideal companion for process engineers, control engineers, and chemists in industry.
Kundenbewertungen
non-linear controller, In-silico system, TITO system, microbial electrolysis cell, microbial fuel cell, MFC, field layer, control layer, core instrumentation, system theory, MEC, configuration methodology, mathematical modeling, CLKF approach