The basic working knowledge for the practicing control engineer in industry, offered here as a handy deluxe edition comprising two volumes each devoted to methods and practical problems.
Focusing on the practical implementation, the methods volume provides readers with rapid access to process modelling and control, while including the theoretical background necessary. Throughout, the essential knowledge is built up from chapter to chapter, starting with laying the foundations in plant instrumentation and control. Modelling abilities are then developed by starting from simple time-loop algorithms and passing on to discrete methods, Laplace transforms, automata and fuzzy logic. In the end, readers have the means to design simple controllers on the basis of their own models, and to use more detailed models to test them. With its clarity and simplicity of presentation, and illustrated by more than 200 diagrams, the volume supports self-study and teaches readers how to apply the appropriate method for the application required, and how to handle problems in process control.
Bridging theory and practice, the second volume contains over 200 practical exercises and their solutions to develop the problem-solving abilities of process engineers. The problems were developed by the author during his many years of teaching at university and are kept brief, taken from the fields of instrumentation, modeling, plant control, control strategy design and stability of control. The algorithm flows and codes, which are mostly based on MATLAB?, are given in many cases and allow for easy translation into applications.
With a clarity and simplicity of presentation, the two volumes are similarly structured for easy orientation.
Applied Process Control: Essential Methods| Michael Mulholland (Author)| Wiley-VCH
Table of Contents
Chapter 1: Introduction
The Idea of Control, Importance of Control in Chemical Processing, Organisation of This Book, Semantics, References.
Chapter 2: Instrumentation
Piping and Instrumentation Diagram Notation, Plant Signal Ranges and Conversions, A Special Note on Differential Pressure Cells, Measurement Instrumentation, Current-to-Pneumatic Transducer, Final Control Elements (Actuators), Controllers, Relays, Trips and Interlocks, Instrument Reliability, References.
Chapter 3: Modelling
General Modelling Strategy, Modelling of Distributed Systems, Modelling Example for a Lumped System: Chlorination Reservoirs, Modelling Example for a Distributed System: Reactor Cooler, Ordinary Differential Equations and System Order, Linearity, Linearisation of the Equations Describing a System, Simple Linearisation ‘Δ’ Concept, Solutions for a System Response Using Simpler Equations, Use of Random Variables in Modelling, Modelling of Closed Loops, References.
Chapter 4: Basic Elements Used in Plant Control Schemes
Signal Filtering/Conditioning, Basic SISO Controllers, Cascade Arrangement of Controllers, Ratio Control, Split Range Control, Control of a Calculated Variable, Use of High Selector or Low Selector on Measurement Signals, Overrides: Use of High Selector or Low Selector on Control Action Signals, Clipping, Interlocks, Trips and Latching, Valve Position Control, Advanced Level Control, Calculation of Closed-Loop Responses: Process Model with Control Element, References.
Chapter 5: Control Strategy Design for Processing Plants
General Guidelines to the Specification of an Overall Plant Control Scheme, Systematic Approaches to the Specification of an Overall Plant Control Scheme, Control Schemes Involving More Complex Interconnections of Basic Elements, References.
Chapter 6: Estimation of Variables and Model Parameters from Plant Data
Estimation of Signal Properties, Real-Time Estimation of Variables for Which a Delayed Measurement Is Available for Correction, Plant Data Reconciliation, Recursive State Estimation, Identification of the Parameters of a Process Model, Combined State and Parameter Observation Based on a System of Differential and Algebraic Equations, Nonparametric Identification, References.
Chapter 7: Advanced Control Algorithms
Discrete z-Domain Minimal Prototype Controllers, Continuous s-Domain MIMO Controller Decoupling Design by Inverse Nyquist Array, Continuous s-Domain MIMO Controller Design Based on Characteristic Loci, Continuous s-Domain MIMO Controller Design Based on Largest Modulus, MIMO Controller Design Based on Pole Placement, State-Space MIMO Controller Design, Concept of Internal Model Control, Predictive Control, Control of Time-Delay Systems, A Note on Adaptive Control and Gain Scheduling, Control Using Artificial Neural Networks, Control Based on Fuzzy Logic, Predictive Control Using Evolutionary Strategies, Control of Hybrid Systems, Decentralised Control, References.
Chapter 8: Stability and Quality of Control
Introduction, View of a Continuous SISO System in the s-Domain, View of a Continuous MIMO System in the s-Domain, View of Continuous SISO and MIMO Systems in Linear State Space, View of Discrete Linear SISO and MIMO Systems, Frequency Response, Control Quality Criteria, Robust Control, References.
Chapter 9: Optimisation
Introduction, Aspects of Optimisation Problems, Linear Programming, Integer Programming and Mixed Integer Programming (MIP), Gradient Searches, Nonlinear Programming and Global Optimisation, Combinatorial Optimisation by Simulated Annealing, Optimisation by Evolutionary Strategies, Mixed Integer Nonlinear Programming, The GAMS® Modelling Environment, Real-Time Optimisation of Whole Plants, References.
Index
LINK FOR THE BOOK
