The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The last decade has seen considerable interest in reviving the fortunes of non linear control. In contrast to the approaches of the 60S, 70S and 80S a very pragmatic agenda for non-linear control is being pursued using the model-based predictive control paradigm. This text by R. Ansari and M. Tade gives an excellent synthesis of this new direction. Two strengths emphasized by the text are: (i) four applications found in refinery processes are used to give the text a firm practical continuity; (ii) a non-linear model-based control architecture is used to give the method a coherent theoretical framework.
Rezensionen / Stimmen
"The book covers many topics. . The book is largely self-contained. It may be useful for the academic control community; also it can serve as a concise reference for technicians interested in the application of nonlinear process control theory related to the petroleum refining industry." (I.Randvee, zbMATH 0953.93006, 2022)
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ISBN-13
978-1-4471-0739-2 (9781447107392)
DOI
10.1007/978-1-4471-0739-2
Schweitzer Klassifikation
1 Introduction.- 1.1 Non-linear Model-based Control.- 1.2 Motivation for this Book.- 1.3 Objectives and Contributions.- 1.4 Scope of the Book.- 1.5 Book Overview.- 2 Literature Review.- 2.1 Introduction.- 2.2 Model-predictive Control.- 2.3 Internal Model Control (IMC).- 2.4 Stability and Robustness of Linear MPC.- 2.5 Non-linear Model-based Control (NMBC).- 2.6 Generic Model Control (GMC).- 2.7 Stability and Robustness of Non-linear System.- 2.8 Conclusions and Discussion.- 3 Inferential Models In Non-linear Multivariable Control Applications.- 3.1 Introduction.- 3.2 Development of Inferential Models.- 3.3 On-line Applications of Inferential Models.- 3.4 Tuning of Inferential Models.- 3.5 Inferential Models in Non-linear Multivariable Control Applications.- 3.6 Benefits of Inferential Models.- 3.7 Conclusions.- 4 Non-linear Model-based Multivariable Control of a Debutanizer.- 4.1 Introduction.- 4.2 The Debutanizer Control Strategy.- 4.3 The Non-linear GMC Control Law.- 4.4 GMC Application to Debutanizer.- 4.5 Model Development.- 4.6 Controller Implementation.- 4.7 Results and Discussions.- 4.8 Cost/Benefit Analysis.- 4.9 Conclusions.- 5 Non-linear Model-based Multivariable Control of a Crude Distillation Process.- 5.1 Introduction.- 5.2 Crude Distillation Process Control Overview.- 5.3 Non-linear Control Algorithm for Fractionator.- 5.4 Model Parameter Update.- 5.5 Model-predictive Control.- 5.6 Results and Discussions.- 5.7 Conclusions.- 6 Constrained Non-linear Multivariable Control of a Catalytic Reforming Process.- 6.1 Introduction.- 6.2 Process Constraints Classifications.- 6.3 Constraint Non-linear Multivariable Control.- 6.4 Application to Catalytic Reforming Process.- 6.5 Real-time Implementation.- 6.6 Conclusions.- 7 Non-linear Multivariable Control of a Fluid Catalytic Cracking Process.- 7.1 Introduction.- 7.2 FCC Process Control Overview.- 7.3 Dynamic Model of FCC Process.- 7.4 Non-linear Control Algorithm for FCC Reactor-Regenerator System.- 7.5 DynamicModel Parameter Update.- 7.6 Model-predictive Control.- 7.7 Real-time Implementation.- 7.8 Plant Results.- 7.9 Conclusions.- 8 Conclusions and Recommendations.- 8.1 Conclusions.- 8.2 Recommendations.- Appendix A.- A.1 Programme for Pressure-compensated Temperature.- A.2 Programme for Naphtha-final-boiling-point Inferential Model.- A.3 Theory Underlying the Pressure-compensated Temperature.- Appendix B.- B.1 S-B GMC Controller Implementation.- Appendix C.- Constrained Multivariable Control System Programme for Shell Heavy Oil Fractionator.- Appendix D.- D.1 Description and Application of Real-time Optimization (RT-Opt.) Software to Catalytic Reforming Reactor Section.- D.1.1 Description.- D.1.2 Mathematical Algorithm.- D.1.3 Application to Catalytic Reforming Reactor Section.- D.2 Implementation Procedure of Real-time Optimization (RT-Opt.).- Appendix E.- Constrained Multivariable Predictive Control for Fluid Catalytic Cracking (FCC) Process.- References.
