Multivariable Industrial Process Identification For Real World Simulation Diagnosis And Control A Practical No Nonsense Guide To Model Based And Data Driven Techniques

Advanced Multivariable Process ID for Real World Simulation
✔️ Single copy: 187 pages, English First Edition, model-based

Identification of Multivariable Industrial Processes presents a unified approach to multivariable industrial process identification, with emphasis on experiment design, model structure, and parameter estimation, plus error bounds of the transfer function. It aims to bridge modern control theory and real-world industrial application, supported by case studies and practical examples.

✅ Author: Zhu, Yucai
✅ Edition: First Edition
✅ Pages: 187
✅ Language: English
✅ Release date: 28-05-1993
✅ Focus: identification of multivariable industrial processes with model-based and data-driven methods

💡 What is multivariable industrial process identification used for in real-world simulation and control?

It helps translate complex plant behavior into practical models for design and analysis.

- multivariable process identification benefits for control system design
- model-based and data-driven approaches for plant simulation
- case studies demonstrating real-world applications
- transfer function estimation and error bounds for robust control
✝️