The CACHE Virtual Process Control Book is intended to provide information on a variety of topics of interest to an undergraduate and/or graduate course on process dynamics and control. 

The current holdings include:

• Introductory Material
• System modeling, linear algebra review
• Linear State Space Systems, controllability, observability
• Stability and control of LTI systems
  
• 2005 CEPAC PASI slides by Crisalle
  

• Multivariable Process  Control
  
• Continuous time systems, frequency response
• RGA, multivariable systems
• SVD, LQR, control and design
• Chapters 1-3 of Multivariable Process Control by Skogestad and Postlethwaite
• Course notes by Huang

• Discrete Modeling and Control
• Z Transform, ARMA Models, Velocity form PID
• Chapters 22-26 Process Dynamics and Control, first edition by Seborg, Edgar, and Mellichamp
  

• Advanced Control and State Estimation
• Control of lumped and distributed parameter systems
  
• State estimation, Kalman filter, stochastic system control
  
• Advanced Process Control by Ray
• Course notes by Edgar
  

• Robust Control
• Performance limitations,
  
• SISO and MIMO IMC
• Robust Process Control by Morari and Zafiriou

• Model Predictive Control
• Constrained optimization
• Linear and nonlinear MPC
• Links to review papers by Morari, Lee, and Henson.  Requires electronic access to journals
• Course notes by Huang
• 2005 CEPAC PASI slides by Lee

• Nonlinear Process Control
• Nonlinear identification
• Differential geometric methods
• Nonlinear state estimation
  
• Nonlinear Process Control, edited by Henson and Seborg.
• Chapter authors include Seborg, Henson, Pearson, Ogunnaike, Doyle, Meadows, Rawlings, Muske, and Edgar
• Book chapter on Nonlinear Control of Industrial Processes by Ogunnaike
  

• Optimal Control
• Use of linear and bilinear matrix inequalities
• Link to paper by VanAntwerp and Braatz.  Requires electronic access to journals

• Dynamic Models
• Matlab models collected by Hedengren
  

Introductory Material

• Basic modeling
  
• Review of linear algebra (slide 31) 
• Matrix exponential (slide 61)
  
• Linear state space (slide 92)
• LTI response (slide 114)
• Matrix transfer function (slide 131)
• Controllability, observability, and stability (slide 152)
• Feedback control of LTI systems (slide 175)
  

Multivariable Process Control

Published by Wiley, 2005, 600 pages. This book is available at amazon.com

• Chapters 1-3
  
• Introduction - Transfer functions, scaling, state space
  
• Classical Feedback Control - Frequency response, closed-loop stability, loop shaping, IMC and PID design
  
• Introduction to Multivariable Control - MIMO transfer functions, Multivariable frequency response, RGA, SVD, MIMO robustness

• LQR, Linear Quadradtic Regulator
  
• Multivariable Control, General
• Multivariable Control, Design
• Control and Design DOF Analysis
  
• Multivariable Control and Design
  
• Multivariable Control, Multi-loop Design

Discrete Modeling and Control

Published by Wiley, 1989, 717 pages.  The more recent second edition is available at amazon.com

• Chapter 22, Sampling and Filtering of Continuous Measurements
  
• Chapter 23, Discrete Time Models
  
• Chapter 24, Dynamic Response of Discrete-Time Systems
  
• Chapter 25, Analysis of Sampled-Data Control Systems
  
• Chapter 26, Design of Digital Controllers
  

Advanced Control and State Estimation

Used copies may be available at amazon.com

• Chapter 1, Preface, Table of Contents, and Introduction
  
• Chapter 2, Online Data Acquisition
  
• Chapter 3, Control of Lumped Parameter Systems
• Chapter 4, Control of Distributed Parameter Systems
• Chapter 5, State Estimation and Stochastic Control
• Chapter 6, Control System Design Case Studies
  

• Recursive least squared estimation
  
• The Kalman Filter

Robust Control

From Robust Process Control by Manfred Morari and Evanghelos Zafiriou.  Published by Prentice Hall, 1989, 488 pages.  Used copies may be available at amazon.com

• Part I, Chapters 1-3, Introduction, SISO Feedback Fundamentals, SISO IMC
  
• Part I, Chapters 4-6, SISO IMC for Stable and Unstable Systems,  Issues
  
• Part II, Chapters 7-9, Sampled Data, sampled SISO IMC, Unstable Sampled IMC
  
• Part III, Chapters 10-11, MIMO Feedback, Robust Stability & Performance
  
• Part III, Chapters 12-14, MIMO IMC, MIMO Performance Limitations, Decentralized
  
• Part IV-V, Chapters 15-16, MIMO Sampled Data, Case Study
• Errata

Model Predictive Control

• MPC

• MPC

Nonlinear Process Control

.

Originally published by Prentice Hall, 1996, 432 pages.  Used copies may be available at amazon.com

• Chapter 1 - Introduction (Dale Seborg and Mike Henson)
  
• Chapter 2 - Nonlinear Process Identification (Ron Pearson and Babatunde Ogunnaike)
  
• Block oriented models, continuous time models
• Discrete-time models
• ARMAX and NARMAX models
• Empirical modeling
  
• Chapter 3 - Nonlinear Systems Theory (Frank Doyle and Mike Henson)
  
• Basic concepts, manifolds, vector fields, inverse and implicit function theorems
• Lie algebra and coordinate transformations
• Nonlinear system inversion and zero dynamics
• Controllability and observability
  
• Chapter 4 - Feedback Linearizing Control (Mike Henson and Dale Seborg)
  
• Input-output linearization
• State-space linearization
• Discrete and sampled data system
  
• Chapter 4 - Feedback Linearizing Control  Smaller pdf file, no figures included.
• Chapter 5 - Model Predictive Control (Edward Meadows and Jim Rawlings)
  
• MPC formulation
• Discrete and continuous model formulations
• Stability
• Chapter 6 - Nonlinear State Estimation (Ken Muske and Tom Edgar)
• Linear state estimation
• Observability
  
• Luenberger Observer, Kalman Filter
• Moving Horizon Estimation
  
• Extended Kalman filter
• Nonlinear moving horizon estimation
  

• Chapter 10, Nonlinear Control of Industrial Processes by Babatunde Ogunnaike

Optimal Control Using Matrix Inequalities

Models and Simulations