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|a 9783642182587
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|a 10.1007/978-3-642-18258-7
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|a Roffel, Brian.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 245 |
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|a Advanced Practical Process Control
|h [electronic resource] /
|c by Brian Roffel, Ben Betlem.
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| 250 |
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|a 1st ed. 2004.
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2004.
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| 300 |
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|a IX, 309 p.
|b online resource.
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|a text
|b txt
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|a text file
|b PDF
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|a Springer eBook Collection
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|a 1 Introduction to Advanced Process Control Concepts -- 1.1 Process Time Constant -- 1.2 Domain Transformations -- 1.3 Laplace Transformation -- 1.4 Discrete Approximations -- 1.5 z-Transforms -- 1.6 Advanced and Modified z-Transforms -- 1.7 Common Elements in Control -- 1.8 The Smith Predictor -- 1.9 Feed-forward Control -- 1.10 Feed-forward Control in a Smith Predictor -- 1.11 Dahlin’s Control Algorithm -- References -- 2 Process Simulation -- 2.1 Simulation using Matlab Simulink -- 2.2 Simulation of Feed-forward Control -- 2.3 Control Simulation of a 2x2 System -- 2.4 Simulation of Dahlin’s Control Algorithm -- 3 Process Modeling and Identification -- 3.1 Model Applications -- 3.2 Types of Models -- 3.3 Empirical (linear) Dynamic Models -- 3.4 Model Structure Considerations -- 3.5 Model Identification -- References -- 4 Identification Examples -- 4.1 SISO Furnace Parametric Model Identification -- 4.2 MISO Parametric Model Identification -- 4.3 MISO Non-parametric Identification of a Non-integrating Process -- 4.4 MIMO Identification of an Integrating and Non-integrating Process -- 4.5 Design of Plant Experiments -- 4.5.1 Nature of Input Sequence -- 4.5.2 PRBS Type Input -- 4.5.3 Step Type Input -- 4.5.4 Type of Experiment -- 4.6 Data File Layout -- 4.7 Conversion of Model Structures -- 4.8 Example and Comparison of Open and Closed Loop Identification -- References -- 5 Linear Multivariable Control -- 5.1 Interaction in Multivariable Systems -- 5.2 Dynamic Matrix Control -- 5.3 Properties of Commercial MPC Packages -- References -- 6 Multivariable Optimal Constraint Control Algorithm -- 6.1 General Overview -- 6.2 Model Formulation for Systems with Dead Time -- 6.3 Model Formulation for Multivariable Processes -- 6.4 Model Formulation for Multivariable Processes with Time Delays -- 6.5 Model Formulation in Case of a Limited Control Horizon -- 6.6 Mocca Control Formulation -- 6.7 Non-linear Transformations -- 6.8 Practical Implementation Guidelines -- 6.9 Case Study -- 6.10 Control of a Fluidized Catalytic Cracker -- 6.11 Examples of Case Studies in MATLAB -- 6.12 Control of Integrating Processes -- 6.13 Lab Exercises -- 6.14 Use of MCPC for Constrained Multivariable Control -- References -- 7 Internal Model Control -- 7.1 Introduction -- 7.2 Factorization of Multiple Delays -- 7.3 Filter Design -- 7.4 Feed-forward IMC -- 7.5 Example of Controller Design -- 7.6 LQ Optimal Inverse Design -- References -- 8 Nonlinear Multivariable Control -- 8.1 Non-linear Model Predictive Control -- 8.2 Non-linear Quadratic DMC -- 8.3 Generic Model Control -- 8.4 Problem Description -- 8.5 GMC Application to the CSTR System -- 8.6 Discussion of the GMC Algorithm -- 8.7 Simulation of Reactor Control -- 8.8 One Step Reference Trajectory Control -- 8.9 Predictive Horizon Reference Trajectory Control -- References -- 9 Optimization of Process Operation -- 9.1 Introduction to Real-time Optimization -- 9.2 Model Building -- 9.3 The Objective Function -- 9.4 Unconstrained Functions: one Dimensional Problems -- 9.5 Unconstrained Multivariable Optimization -- 9.6 Linear Programming -- 9.7 Non-linear Programming -- References -- 10 Optimization Examples -- 10.1 AMPL: a Multi-purpose Optimizer -- 10.2 Optimization Examples -- References -- 11 Integration of Control and Optimization -- 11.1 Introduction -- 11.2 Description of the Desalination Plant -- 11.3 Production Maximization of Desalination Plant -- 11.4 Linear Model Predictive Control of Desalination Plant -- 11.5 Reactor problem definition -- 11.6 Multivariable Non-linear Control of the Reactor -- References -- Appendix I. MCPC software guide -- I.1 Installation -- I.2 Model identification -- I.2.1 General process information -- I.2.2 Identification data -- I.2.3 Output details -- I.3 Controller design -- I.4 Control simulation -- I.5 Dealing with constraints -- I.6 Saving a project -- Appendix II. Comparison of control strategies for a hollow shaft reactor -- II.1 Introduction -- II.2 Model Equations -- II.3 Proportional Integral Control -- II.4 Linear Multivariable Control -- II.5 Non-linear Multivariable Control -- References.
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| 520 |
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|a This text and reference offers an application-oriented approach to process control. It systematically explains process identification, control and optimization, the three key steps needed to solve a multivariable control problem. Theory is discussed as far as it is needed to understand and solve the defined problem, while numerous examples written in MATLAB illustrate the problem-solving approach.
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| 590 |
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|a Loaded electronically.
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| 590 |
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|a Electronic access restricted to members of the Holy Cross Community.
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| 650 |
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|a Electrical engineering.
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| 650 |
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0 |
|a Control engineering.
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| 650 |
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0 |
|a Robotics.
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| 650 |
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0 |
|a Mechatronics.
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| 650 |
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|a Chemical engineering.
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| 650 |
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|a Computational intelligence.
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| 650 |
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|a Vibration.
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| 650 |
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|a Dynamical systems.
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| 650 |
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|a Dynamics.
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| 690 |
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|a Electronic resources (E-books)
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| 700 |
1 |
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|a Betlem, Ben.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 830 |
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|a Springer eBook Collection.
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