MPG.eBooks - Table of Contents: Optimisation of Industrial Processes at Supervisory Level

Read Now

Optimisation of Industrial Processes at Supervisory Level Application to Control of Thermal Power Plants

In the increasingly competitive modern world, the industrial sector faces new challenges such as improving productivity and reducing costs while taking into account the process operational constraints. As energy demand increases in many countries, especially in big cities where the environmental con...

Full description

Bibliographic Details
Main Authors:	Saez, Doris A., Cipriano, Aldo (Author), Ordys, Andrzej W. (Author)
Format:	eBook
Language:	English
Published:	London Springer London 2002, 2002
Edition:	1st ed. 2002
Series:	Advances in Industrial Control
Subjects:	Electric Power Production Machines, Tools, Processes Control And Systems Theory Manufactures Control Engineering Electrical Power Engineering
Online Access:	https://doi.org/10.1007/978-1-4471-0113-0?nosfx=y
Collection:	Springer Book Archives -2004 - Collection details see MPG.ReNa

Table of Contents:

Content
1. Introduction
2. Non-linear Dynamic Modelling for Control Design
2.1 Introduction
2.2 Fundamentals of Fuzzy Logic
2.3 Dynamic Models Based on Fuzzy Logic
2.4 Parameters Estimation
2.5 Structure Identification
2.6 Discussion
2.7 A New Structure Identification Method for Fuzzy Models
3. Non-linear Predictive Control
3.1 Fundamentals of Predictive Control
3.2 Literature Review
3.3 Prediction from Linear Models
3.4 Linear Predictive Control Algorithms
3.5 Prediction for Non-linear Models
3.6 Non-linear Predictive Control
3.7 Discussion
4. Supervisory Optimal Control for a Pre-specified Regulatory Level
4.1 Problem Statement
4.2 Alternative Solutions
4.3 Supervisory Controller Design Based on Linear Models
4.4 Supervisory Controller Design Based on Non-linear Models
4.5 Application to a Boiler System
4.6 Discussion
5. Application to the Control of Thermal Power Plants
5.1 Modelling and Simulation of a Combined Cycle Power Plant
5.2 Control of Thermal Power Plant Boiler
6. Discussion and Conclusions
Appendix A. Sensitivity Analysis Program
Appendix B. Prediction of Controlled Variables and Manipulated Variables
B.1 Prediction of Controlled Variables
B.2 Prediction of Manipulated Variables
Appendix C. Special Cases of Polynomial Cancellations
C.1 A Quadratic Objective Function of the Manipulated Variables at the Supervisory Level
C.2 A GPC Objective Function at the Supervisory Level
Appendix D. Supervisory Controller Programs
D.1 Direct Method
D.2 Indirect Method
D.3 One-step Fuzzy Predictor
D.4 Multi-step Fuzzy Predictor
Appendix E. Main Variables of a Combined Cycle Thermal Power Plant
E.1 Boiler
E.1.1 Furnace
E.1.2 Risers
E.1.3 Drum
E.1.4 Superheater
E.1.5 Reheater
E.1.6 Economiser
E.2 Steam Turbine
E.2.1 The High Pressure Turbine
E.2.2 The Intermediate Pressure Turbine
E.2.3 The Low Pressure Turbine
E.2.4 Steam Turbine
E.3 Gas Turbine
E.3.1 Compressor
E.3.2 Combustion Chamber
E.3.3 Turbine
Appendix F. Simulator Programs in MATLAB®-SIMULINK®
F.1 Boiler
F.1.1 Furnace
F.1.2 Risers
F.1.3 Drum
F.1.4 Superheater
F.1.5 Reheater
F.1.6 Economiser
F.2 Steam Turbine
F.2.1 The High Pressure Turbine
F.2.2 The Intermediate Pressure Turbine
F.2.3 The Low Pressure Turbine
F.3 Gas Turbine
F.3.1 Compressor
F.3.2 Combustion Chamber
F.3.3 Turbine
References

Optimisation of Industrial Processes at Supervisory Level Application to Control of Thermal Power Plants

Similar Items