Non-Linear Model-Based Process Control : Applications in Petroleum Refining

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