From ControlsWiki

Welcome to the University of Michigan Chemical Engineering Process Dynamics and Controls Open Textbook. This electronic textbook is a student-contributed open-source text covering the materials used at Michigan in our senior level controls course. Click here for the 2007 version, and here for the 2006 version of the text.
Follow this link to find more information about this course.

Lectures

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Recorded video lectures by Prof. Peter Woolf, and lecture materials for the course, are freely available online. These lectures are available here.

Chemical Process Dynamics and Controls Text

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Contents 1 Modeling Basics 2 Sensors and Actuators 3 Piping and Instrumentation Diagrams 4 Logical Modeling 5 Modeling Case Studies 6 Chemical Process Controls 6.1 Process Controls Basics 6.2 PID control 6.3 Dynamical Systems Analysis 6.4 Control Architectures 6.5 MIMO Control 7 Statistical Analysis for Chemical Process Control 7.1 Statistics and Probability Background 7.2 Statistical Process Control 7.3 Design of Experiments 7.4 Bayesian Networks

Modeling Basics

1. Verbal modeling: process description, control specifications, and connections
2. Incidence graphs: interpretations, consistency, and inconsistency
3. Excel modeling: logical models, optimization with solver for nonlinear regression, sampling random numbers
4. Noise modeling: more detailed information on noise modeling: white, pink, and brown noise, pops and crackles
5. Numerical ODE solving in Excel: Euler’s method, Runge Kutta, Dead time in ODE solving
6. Solving ODEs with Mathematica: How to find numerical and analytical solutions to ODEs with Mathematica
7. Fitting ODE parameters to data using Excel: Using regression to fit complex models in Excel
8. Helpful Mathematica Syntax: Hints on how to use Mathematica to model chemical processes

Sensors and Actuators

1. Temperature sensors
2. Pressure sensors
3. Level sensors
4. Flow sensors
5. Composition sensors
6. pH and viscosity sensors
7. Valves: types, kinds, and selection
8. Valves: modeling dynamics

More information on sensors and actuators at ECOSSE

Piping and Instrumentation Diagrams

1. P&ID general information
2. P&ID standard notation
3. P&ID standard structures, location of features
4. P&ID standard pitfalls
5. Safety features in P&ID
6. Regulatory Agencies and Compliance

Logical Modeling

1. Boolean models: truth tables and state transition diagrams
2. Logical control programs: IF.. THEN.., WHILE..

Modeling Case Studies

1. Surge tank model
2. Heated surge tank see also ECOSSE
3. Bacterial chemostat
4. ODE & Excel CSTR model w/ heat exchange
5. ODE & Excel model of a simple distillation column
6. ODE & Excel model of a heat exchanger
7. ODE & Excel model of an adiabatic PFR
8. Cruise control for an electric vehicle

More information on chemical process modeling in general at ECOSSE example 1 and ECOSSE example 2

Chemical Process Controls

Process Controls Basics

1. Introduction to Controls
2. Introduction to DCS
3. Dirac delta (impulse) function (10/09)
4. First-order differential equations (10/09)
5. Second-order differential equations (10/13)
6. Taylor Series

PID control

1. P, I, D, PI, PD, and PID control see also ECOSSE
2. PID tuning via classical methods See also ECOSSE
3. PID tuning via optimization
4. PID downsides and solutions See also ECOSSE

Dynamical Systems Analysis

1. Finding fixed points in ODEs and Boolean models
2. Linearizing ODEs
3. Eigenvalues and Eigenvectors
4. Using eigenvalues and eigenvectors to find stability and solve ODEs
5. Phase plane analysis: attractors, spirals, limit cycles
6. Root locus plots: effect of tuning
7. Routh stability: ranges of parameter values that are stable

Control Architectures

1. Feedback control: What is it? When useful? When not? Common usage.
2. Feed forward control: What is it? When useful? When not? Common usage. see also ECOSSE
3. Cascade control: What is it? When useful? When not? Common usage.
4. Ratio control: What is it? When useful? When not? Common usage.
5. Summary: Summary on Control Architectures' philosophies, advantages, and disadvantages.
6. Common control loops / model for liquid pressure and liquid level see also ECOSSE
7. Common control loops / model for temperature control
8. Common control architectures / model for reactors

MIMO Control

1. Determining if a system can be decoupled
2. MIMO control using RGA see also ECOSSE
3. MIMO using model predictive control
4. Neural Networks for automatic model construction

Statistical Analysis for Chemical Process Control

Statistics and Probability Background

1. Basic statistics: mean, median, average, standard deviation, z-scores, and p-value
2. Six Sigma: What is it and what does it mean?
3. Bayes Rule, conditional probability, independence
4. Occasionally dishonest casino?: Markov chains and hidden Markov models
5. Continuous Distributions: normal and exponential
6. Discrete Distributions: hypergeometric, binomial, and poisson
7. Multinomial distributions
8. Comparisons of two means
9. Factor analysis and ANOVA
10. Correlation and mutual information
11. Random sampling from a stationary Gaussian process

Statistical Process Control

1. SPC: Basic Control Charts: Theory and Construction, Sample Size, X-Bar, R charts, S charts

Design of Experiments

1. Design of experiments via Taguchi methods: orthogonal arrays
2. Design of experiments via factorial designs
3. Design of experiments via random design

Bayesian Networks

1. Bayesian network theory
2. Learning and analyzing Bayesian networks with Genie