Table of Contents

Practical Process Control
Proven Methods and Best Practices for Automatic PID Control
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I. Modern Control  is Based on Process Dynamic Behavior (by Doug Cooper)

 1) Fundamental Principles of Process Control
     Motivation and Terminology of Automatic Process Control
     The Components of a Control Loop
     Process Data, Dynamic Modeling and a Recipe for Profitable Control
     Sample Time Impacts Controller Performance

 2) Graphical Modeling of Process Dynamics: Heat Exchanger Case Study
     Step Test Data From the Heat Exchanger Process
     Process Gain is the “How Far” Variable
     Process Time Constant is the “How Fast” Variable
     Dead Time is the “How Much Delay” Variable
     Validating Our Heat Exchanger Process FOPDT Model

 3) Modeling Process Dynamics: Gravity Drained Tanks Case Study
     The Gravity Drained Tanks Process
     Dynamic "Bump" Testing of the Gravity Drained Tanks Process
     Graphical Modeling of Gravity Drained Tanks Step Test
     Modeling Gravity Drained Tanks Data Using Software

 4) Software Modeling of Process Dynamics: Jacketed Stirred Reactor Case Study
     Design Level of Operation for the Jacketed Stirred Reactor Process
     Modeling the Dynamics of the Jacketed Stirred Reactor with Software
     Exploring the FOPDT Model With a Parameter Sensitivity Study
 

II. PID Controller Design and Tuning (by Doug Cooper)

 5) Process Control Preliminaries
     Design and Tuning Recipe Must Consider Nonlinear Process Behavior
     A Controller’s “Process” Goes From Wire Out to Wire In
     The Normal or Standard PID Algorithm

 6) Proportional Control - The Simplest PID Controller
     The P-Only Control Algorithm
     P-Only Control of the Heat Exchanger Shows Offset
     P-Only Disturbance Rejection of the Gravity Drained Tanks  

 7) Caution: Pay Attention to Units and Scaling
     Controller Gain is Dimensionless in Commercial Systems

 8) Integral Action and PI Control
     Integral Action and PI Control
     PI Control of the Heat Exchanger
     PI Disturbance Rejection of the Gravity Drained Tanks 
     The Challenge of Interacting Tuning Parameters
     PI Disturbance Rejection in the Jacketed Stirred Reactor 
     Integral (Reset) Windup, Jacketing Logic and the Velocity PI Form

 9) Derivative Action and PID Control
     PID Control and Derivative on Measurement
     The Chaos of Commercial PID Control
     PID Control of the Heat Exchanger
     Measurement Noise Degrades Derivative Action
     PID Disturbance Rejection of the Gravity Drained Tanks

10) Signal Filters and the PID with Controller Output Filter Algorithm
     Using Signal Filters In Our PID Loop
     PID with Controller Output (CO) Filter
     PID with CO Filter Control of the Heat Exchanger
     PID with CO Filter Disturbance Rejection in the Jacketed Stirred Reactor
 

III. Additional PID Design and Tuning Concepts (by Doug Cooper)

11) Exploring Deeper: Sample Time, Parameter Scheduling, Plant-Wide Control
     Sample Time is a Fundamental Design and Tuning Specification
     Parameter Scheduling and Adaptive Control of Nonlinear Processes
     Plant-Wide Control Requires a Strong PID Foundation

12) Controller Tuning Using Closed-Loop (Automatic Mode) Data
     Ziegler-Nichols Closed-Loop Method a Poor Choice for Production Processes
     Controller Tuning Using Set Point Driven Data 
     Do Not Use Disturbance Driven Data for Controller Tuning 

13) Evaluating Controller Performance
     Comparing Controller Performance Using Response Plot Data
 

IV. Control of Integrating Processes (by Doug Cooper & Bob Rice)

14) Integrating (Non-Self Regulating) Processes
     Recognizing Integrating (Non-Self Regulating) Process Behavior
     A Design and Tuning Recipe for Integrating Processes
     Analyzing Pumped Tank Dynamics with a FOPDT Integrating Model
     PI Control of the Integrating Pumped Tank Process
 

V. Advanced Classical Control Architectures (by Doug Cooper & Allen Houtz)

15) Cascade Control For Improved Disturbance Rejection
     The Cascade Control Architecture
     An Implementation Recipe for Cascade Control
     A Cascade Control Architecture for the Jacketed Stirred Reactor
     Cascade Disturbance Rejection in the Jacketed Stirred Reactor

16) Feed Forward with Feedback Trim For Improved Disturbance Rejection
     The Feed Forward Controller
     Feed Forward Uses Models Within the Controller Architecture  
     Static Feed Forward and Disturbance Rejection in the Jacketed Reactor

17) Ratio, Override and Cross-Limiting Control
     The Ratio Control Architecture
     Ratio Control and Metered-Air Combustion Processes
     Override (Select) Elements and Their Use in Ratio Control
     Ratio with Cross-Limiting Override Control of a Combustion Process

18) Cascade, Feed Forward and Three-Element Control
     Cascade, Feed Forward and Steam Boiler Level Control
     Dynamic Shrink/Swell and Steam Boiler Level Control
 

VI. Process Applications in Control

19) Distillation Column Control (by Jim Riggs)
     Introduction to Distillation Column Control
     Major Disturbances & First-Level Distillation Column Control
     Inferential Temperature & Single-Ended Column Control
     Dual Composition Control & Constraint Distillation Column Control  

20) Discrete Time Modeling of Dynamic Systems (by Peter Nachtwey)
     A Discrete Time Linear Model of the Heat Exchanger

21) Fuzzy Logic and Process Control (by Fred Thomassom)
     Envelope Optimization and Control Using Fuzzy Logic