Nonlinear Model-Based Process Control : Applications in Petroleum Refining

by Ansari, Rashid M.; Tade, Moses O.

• ISBN13: 9781852332136
• ISBN10: 1852332131
• Edition: 1st
• Format: Hardcover
• Copyright: 2000-04-01
• Publisher: Springer Verlag

Summary

The work in this book entails the development of non-linear model-based multivariable control algorithms and strategies and their use in an integrated approach to control strategy, which incorporates a process model, an inferential model and a multivariable control algorithm in one framework. This integrated approach has been applied to various refinery processes that exhibit strong non-linearities, process interactions and constraints and has been shown to produce good results by improving closed-loop quality control and maximising the yield of high-value products. The non-linear model-based control structure is further extended to permit the use of inferential models in non-linear multivariable control applications. A wide range of inferential models has been developed, implemented in real-time and integrated with non-linear multivariable control applications. These inferential models demonstrate the improvement in the performance of closed-loop quality control and the dynamic response of the system in reducing long time delays. A comlex multivariable control problem is solved by formulating the non-linear, constrained optimisation strategy for a crude distillation and a semi-regenerative catalytic reforming process. A non-linear constrained optimisation strategy is proposed and applied to a fluid catalytic cracking reactor-regenerator section using a simplified fluid-catalytic-cracking-process model. A dynamic parameter update algorithm is developed and used to reduce the effect of larger modelling errors by updating the selected model parameters regularly. This book was brought about, primarily, in response to industrial interest in the improvement of operating efficiency and profitability using the non-linear model-based technology which it discusses. A second motivation of more academic interest was the implementation of model-based methods in real-time for control of complex processes with strong non-linearities and process interactions and a third, more practical, was the reduction of the gap between theoretical work and the industrisl practice of advanced process control.

Table of Contents

List of Figures	xix
List of Tables	xxiii
Introduction	1	(6)
Non-linear Model-based Control	1	(1)
Motivation for this Book	2	(1)
Objectives and Contributions	2	(1)
Objectives	2	(1)
Contributions	2	(1)
Non-linear Control Theory and Development	2	(1)
Practical Applications in Industries	3	(1)
Scope of the Book	3	(1)
Book Overview	4	(3)
Literature Review	7	(34)
Introduction	7	(3)
Industrial Background	8	(1)
Academic Background	9	(1)
Model-predictive Control	10	(7)
Dynamic Matrix Control (DMC)	10	(2)
Limitations of DMC	12	(2)
Model Algorithm Control (MAC)	14	(2)
Difference Between DMC and MAC	16	(1)
Principal Component Analysis (PCA)	16	(1)
Internal Model Control (IMC)	17	(4)
IMC Theoretical Background	17	(2)
Comparison of IMC with DMC and MAC	19	(1)
Extensions and Variants of IMC	20	(1)
Stability and Robustness of Linear MPC	21	(2)
Non-linear Model-based Control (NMBC)	23	(7)
Introduction	23	(1)
Non-linear Model-based Control Architecture	24	(1)
NMBC-Model	24	(2)
NMBC-Model Parameter Update	26	(1)
NMBC-Controller Configuration/Simulation	26	(1)
Non-linear Control System Technique	27	(2)
Non-linear Programming Methods	29	(1)
Generic Model Control (GMC)	30	(6)
Introduction	30	(2)
GMC and Internal Model Control (IMC)	32	(2)
GMC and Model-predictive Control (MPC)	34	(1)
Discrete form of GMC	34	(1)
Relationship between Discrete GMC and MPC	35	(1)
Stability and Robustness of Non-linear System	36	(2)
Conclusions and Discussion	38	(3)
Inferential Models In Non-linear Multivariable Control Applications	41	(18)
Introduction	41	(2)
Development of Inferential Models	43	(4)
Overview of Models	43	(2)
Non-linear Inferential Control Model	45	(1)
Correlation-Based Model	45	(1)
Verification of Correlation-Based Model	46	(1)
On-line Applications of Inferential Models	47	(7)
Naphtha Final Boiling Point (FBP) of Crude Distillation	47	(2)
Kerosene Flash Point of Crude Distillation	49	(2)
Reid Vapour Pressure (RVP) of Debutanizer Bottom	51	(1)
Iso-Pentane of Debutanizer Overhead	51	(2)
Octane Inferential Model for Catalytic Reforming	53	(1)
Tuning of Inferential Models	54	(1)
Inferential Models in Non-linear Multivariable Control Applications	55	(2)
Benefits of Inferential Models	57	(1)
Conclusions	57	(2)
Non-linear Model-based Multivariable Control of a Debutanizer	59	(20)
Introduction	59	(2)
The Debutanizer Control Strategy	61	(3)
Objective	61	(1)
Process Description	61	(1)
Control Proposal	62	(2)
Hardware Consideration	64	(1)
The Non-linear GMC Control Law	64	(1)
GMC Application to Debutanizer	65	(3)
Model Development	68	(3)
Steady-State Model Considerations	68	(1)
Development of Inferential Models	68	(1)
RVP of Platformer Feed	69	(1)
Iso-pentane of the Debutanizer Overhead	70	(1)
Controller Implementation	71	(5)
Controller-Process Interface	71	(3)
Non-linear Controller Tuning	74	(2)
Results and Discussions	76	(1)
Cost/Benefit Analysis	77	(1)
Benefits Calculations	78	(1)
Conclusions	78	(1)
Non-linear Model-based Multivariable Control of a Crude Distillation Process	79	(32)
Introduction	79	(1)
Crude Distillation Process Control Overview	80	(7)
Process Description	80	(2)
Control Objectives and Constraints	82	(2)
Control Objectives	84	(1)
Control Constraints	84	(1)
Dynamic Model with Uncertainty	84	(3)
Non-linear Control Algorithm for Fractionator	87	(3)
Model Parameter Update	90	(1)
Model-predictive Control	91	(3)
Problem Formulation for Linear Control	91	(1)
MATLAB®/SIMULINK® Programme	92	(2)
Results and Discussions	94	(14)
Simulation Results	94	(1)
Integrating Top End Point Inferential Model	95	(12)
Real--time Implementation Results	107	(1)
Conclusions	108	(3)
Constrained Non-linear Multivariable Control of a Catalytic Reforming Process	111	(32)
Introduction	111	(2)
Process Constraints Classifications	113	(2)
Constraint Non-linear Multivariable Control	115	(6)
Control Theory and Design	115	(5)
Selection of Design Parameters	120	(1)
Selection of K1C and K2C	120	(1)
Selection of W	120	(1)
Application to Catalytic Reforming Process	121	(12)
Dynamic Model of the Process	121	(1)
Introduction	121	(1)
Model Development	122	(2)
Numerical Integration	124	(1)
Results and Discussion	124	(2)
Conclusions	126	(1)
Non-linear Control Algorithm for Reforming Reactors	126	(1)
Problem Formulation	126	(3)
Constrained Non-linear Optimization Problem	129	(2)
Non-linear Control Objectives and Strategies	131	(1)
Control Objectives	131	(1)
WAIT/Octane Control Strategies	132	(1)
Real-time Implementation	133	(8)
Non-linear Controller Tuning	134	(1)
Results and Discussions	135	(6)
Conclusions	141	(2)
Non-linear Multivariable Control of a Fluid Catalytic Cracking Process	143	(40)
Introduction	143	(3)
FCC Process Control Overview	146	(2)
Process Description	146	(1)
Economic Objectives and Non-linear Control Strategies	147	(1)
Dynamic Model of FCC Process	148	(6)
Model Development	148	(2)
Riser and Reactor Section	150	(1)
Regenerator Section	150	(2)
Results and Discussions	152	(2)
Non-linear Control Algorithm for FCC Reactor-Regenerator System	154	(3)
Dynamic Model Parameter Update	157	(6)
Introduction	157	(1)
Development of Model Parameter Update System	158	(2)
Parameter Update Algorithm	160	(1)
Application to FCC Process	161	(2)
Model-predictive Control	163	(4)
Problem Formulation for Linear Control	163	(1)
Signal Conditioning	163	(1)
Prediction Trend Correction	163	(1)
Control Move Calculation	164	(1)
Process Identification Tests	165	(1)
Combustion-air-flow Models	166	(1)
Feed-flow-rate Models	166	(1)
Feed-preheat-temperature Models	166	(1)
Riser-outlet-temperature Models	166	(1)
Real-time Implementation	167	(12)
Non-linear Controller Tuning	168	(1)
Controller Interface to DCS System	168	(1)
Results and Discussions	169	(6)
Comparison of Non-linear Control with DMC	175	(4)
Plant Results	179	(2)
Conclusions	181	(2)
Conclusions and Recommendations	183	(6)
Conclusions	183	(3)
Summary of Results Achieved	183	(1)
Outline of the Major Contributions of this Research	184	(2)
Recommendations	186	(3)
Embedded Optimization for Non-linear Control	186	(1)
Non-linear Nonminimum Phase Systems	187	(1)
Robust Stability and Performance of Non-linear Systems	187	(1)
On-line Parameter Estimation (Model Adaptation)	187	(2)
Appendix A	189	(4)
A.1 Programme for Pressure-compensated Temperature	189	(1)
A.2 Programme for Naphtha-final-boiling-point Inferential Model	189	(1)
A.3 Theory Underlying the Pressure-compensated Temperature	190	(3)
Appendix B	193	(2)
B.1 S-B GMC Controller Implementation	193	(2)
Appendix C	195	(6)
Constrained Multivariable Control System Programme for Shell Heavy Oil Fractionator	195	(6)
Appendix D	201	(4)
D.1 Description and Application of Real-time Optimization (RT-Opt.) Software to Catalytic Reforming Reactor Section	201	(2)
D.1.1 Description	201	(1)
D.1.2 Mathematical Algorithm	202	(1)
D.1.3 Application to Catalytic Reforming Reactor Section	202	(1)
D.2 Implementation Procedure of Real-time Optimization (RT-Opt.)	203	(2)
Appendix E	205	(4)
Constrained Multivariable Predictive Control for Fluid Catalytic Cracking (FCC) Process	205	(4)
References	209	(18)
Index	227