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Chemical Process Dynamics and Controls

This textbook is a student-contributed open-source text covering the materials used in the senior level controls course. The authors cover a variety of approaches to reduce or manage this uncertainty through the use of robust designs, dynamic systems theory, nonlinear dynamics, control theory, and statistics.

Industrial and Systems Engineering Engineering

Author: Peter Woolf et al.
Publisher: University of Michigan
Source: LibreTexts
License: CC BY
Language: EN

Read online Download PDF (open licence)

Contents· 106 sections

01: Overview
1.01: Introduction to Controls- Background and design methodology
1.02: Introduction to DCS- Control system hardware
1.03: Current Significance- Process controls and you
1.04: Failures in Process Control- Bhopal Three Mile Island
1.05: Process Controls in Everyday Life- Applying process control thinking to everyday situations
02: Modeling Basics
2.01: Verbal Modeling- process description control specifications and connections
2.02: Degrees of Freedom- importance calculation procedure and examples
2.03: Incidence Graphs- interpretations consistency and inconsistency
2.04: Excel modeling- logical models optimization with solver for nonlinear regression sampling random numbers
2.05: Noise modeling- more detailed information on noise modeling- white pink and brown noise pops and crackles
2.06: Numerical ODE solving in Excel- Eulers method Runge Kutta Dead time in ODE solving
2.07: Solving ODEs with Mathematica- How to find numerical and analytical solutions to ODEs with Mathematica
2.08: Fitting ODE parameters to data using Excel- Using regression to fit complex models in Excel
2.09: Helpful Mathematica Syntax- Hints on how to use Mathematica to model chemical processes
03: Sensors and Actuators
3.01: Control systems- Measurement Devices
3.02: Temperature Sensors
3.03: Pressure Sensors
3.04: Level Sensors
3.05: Flow Sensors
3.06: Composition Sensors
3.07: pH and Viscosity Sensors
3.08: Miscellaneous Sensors
3.09: Valves - Types Kinds and Selection
3.10: Valves - Modeling Dynamics
04: Piping and Instrumentation Diagrams
4.01: PandID General Information
4.02: Piping and Instrumentation Diagram Standard Notation
4.03: Piping and Instrumentation Diagrams- Location of Controls and Standard Control Structures
4.04: Piping and Instrumentation Diagrams - Standard Pitfalls
4.05: Safety Features in Piping and Instrumentation Diagrams
4.06: Regulatory Agencies and Compliance
05: Logical Modeling
5.01: Boolean Models - Truth Tables and State Transition Diagrams
5.02: Logical control programs- IF... THEN WHILE
06: Modeling Case Studies
6.01: Surge Tank Model
6.02: Heated Surge Tank
6.03: Bacterial Chemostat
6.04: ODE and Excel CSTR model with heat exchange
6.05: ODE and Excel model of a Simple Distillation Column
6.06: ODE and Excel model of a Heat Exchanger
6.07: ODE and Excel Model of an Adiabatic PFR
6.08: Modeling and PID Controller Example - Cruise Control for an Electric Vehicle
6.09: Blood Glucose Control in Diabetic Patients
07: Mathematics for Control Systems
7.01: Dirac delta (impulse) function
7.02: First-order differential equations
7.03: Second-order differential equations
7.04: Taylor Series
7.05: Laplace Transforms
08: Optimization
8.01: Optimization
8.02: Linear Optimization
8.03: Non-linear Optimization
09: Proportional-Integral-Derivative (PID) Control
9.01: Constructing Block Diagrams- Visualizing control measurements
9.02: P I D PI PD and PID control
9.03: PID Tuning via Classical Methods
9.04: PID tuning via Frequency Responses with Bode Plots
9.05: PID tuning via optimization
9.06: PID Downsides and Solutions
10: Dynamical Systems Analysis
10.01: Finding fixed points in ODEs and Boolean models
10.02: Linearizing ODEs
10.03: Eigenvalues and Eigenvectors
10.04: Using eigenvalues and eigenvectors to find stability and solve ODEs
10.05: Phase Plane Analysis - Attractors Spirals and Limit cycles
10.06: Root locus plots- effect of tuning
10.07: Routh stability- ranges of parameter values that are stable
11: Control Architectures
11.01: Feedback control- What is it When useful When not Common usage.
11.02: Feed forward control- What is it When useful When not Common usage.
11.03: Cascade control- What is it When useful When not Common usage.
11.04: Ratio control- What is it When useful When not Common usage.
11.05: Common control loops and model for liquid pressure and liquid level
11.06: Common control loops and model for temperature control
11.07: Common control architectures and model for reactors
12: Multiple Input Multiple Output (MIMO) Control
12.01: Determining if a system can be decoupled
12.02: MIMO control using RGA
12.03: MIMO using model predictive control
12.04: Neural Networks for automatic model construction
12.05: Understanding MIMO Control Through Two Tanks Interaction
13: Statistics and Probability Background
13.01: Basic statistics- mean median average standard deviation z-scores and p-value
13.02: SPC- Basic Control Charts- Theory and Construction Sample Size X-Bar R charts S charts
13.03: Six Sigma- What is it and what does it mean
13.04: Bayes Rule conditional probability independence
13.05: Bayesian network theory
13.06: Learning and analyzing Bayesian networks with Genie
13.07: Occasionally dishonest casino- Markov chains and hidden Markov models
13.08: Continuous Distributions- normal and exponential
13.09: Discrete Distributions- hypergeometric binomial and poisson
13.10: Multinomial Distributions
13.11: Comparisons of two means
13.12: Factor analysis and ANOVA
13.13: Correlation and Mutual Information
13.14: Random sampling from a stationary Gaussian process
14: Design of Experiments
14.01: Design of Experiments via Taguchi Methods - Orthogonal Arrays
14.02: Design of experiments via factorial designs
14.03: Design of Experiments via Random Design
14.04: Summary- Summary on Control Architectures philosophies advantages and disadvantages.