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CBE 30338 Data Analytics, Optimization, and Control - Home
  • CBE 30338 Data Analytics, Optimization, and Control

Course Information

  • Syllabus
  • Schedule (2025)
  • Assignments
    • Homework 1: Computing and Data Analysis Review
    • Lab 1: Step Test of a First-Order System
    • Lab 2: Model Identification
    • Lab 3: Relay (On-Off) Control
    • Lab 4: PI Control
    • Homework 2: Optimization
    • Lab 5: Open Loop Optimization
    • Lab 6: Model Predictive Control (MPC)

Topical Materials

  • 1. What is Process Control?
    • 1.1. What is Feedback?
    • 1.2. Elements of Process Control
  • 2. Process Modeling
    • 2.1. One Compartment Pharmacokinetics
    • 2.2. First-Order Linear Systems
    • 2.3. First Order Model for a Single Heater
    • 2.4. Fitting a Model to Experimental Data
    • 2.5. Second Order Model
    • 2.6. Fed-Batch Bioreactor
    • 2.7. Characteristics of Second Order Systems
    • 2.8. Exothermic Continuous Stirred Tank Reactor
    • 2.9. Hare and Lynx Population Dynamics
    • 2.10. Study Guide
  • 3. Feedback Control
    • 3.1. Case Study: Thermal Cycling for PCR
    • 3.2. Setpoints
    • 3.3. Case Study: PCR Thermal Cycler Protocols
    • 3.4. Relay Control
    • 3.5. Implementing Controllers in Python
    • 3.6. Practical Proportional (P) and Proportional-Integral (PI) Control
    • 3.7. Analysis of Proportional Only Controller
    • 3.8. Analysis of Proportional-Integral Controller
    • 3.9. Integral Windup and Bumpless Transfer
    • 3.10. Analysis of Velocity-Form Bumpless PI Controller
    • 3.11. Controller Tuning
  • 4. Process Analytics
    • 4.1. Learning Goals
    • 4.2. Data/Process/Operational Historian
    • 4.3. State Estimation
    • 4.4. Lab Assignment 5: State Estimation
    • 4.5. Anomaly Detection
    • 4.6. Lab Assignment 6: Anomaly Detection
    • 4.7. Observer Synthesis using Linear Matrix Inequalities
    • 4.8. Application of Luenberger Observers to Environmental Modeling of Rivers
    • 4.9. Study Questions
  • 5. Optimization
    • 5.1. Linear Production Model
    • 5.2. Linear Blending Problems
    • 5.3. Homework 2: Optimization (Legacy)
    • 5.4. Gasoline Blending
    • 5.5. Linear Programming
    • 5.6. Design of a Cold Weather Fuel
    • 5.7. Pyomo Examples
    • 5.8. Recharging Strategy for an Electric Vehicle
    • 5.9. Pooling and Blending
  • 6. Predictive Control
    • 6.1. Static Operability
    • 6.2. Open-Loop Optimal Control
    • 6.3. Predictive Control
    • 6.4. Implementing Predictive Control
    • 6.5. Gompertz Model
    • 6.6. Project: Gompertz Model for Tumor Growth
    • 6.7. Time as a Decision Variable
    • 6.8. TCLab: Open-Loop Optimization and Estimation using Pyomo
    • 6.9. TCLab: Model Predictive Control (MPC)
    • 6.10. Simulation and Optimal Control in Pharmacokinetics
  • 7. Projects (Spring 2023)
    • 7.1. Project Ideas
  • 8. References

Control Laboratory

  • 1. The Temperature Control Laboratory
    • 1.1. Setting up TCLab
    • 1.2. Testing and Troubleshooting TCLab
    • 1.3. Python Coding for TCLab
    • 1.4. Testing Your Software Environment and TCLab
  • 2. Step Testing
    • 2.1. Step Testing
    • 2.2. Lab Assignment 1: Step Test of a First-Order System
  • 3. Empirical Model Identification
    • 3.1. Fitting Step Test Data to Empirical Models
  • 4. Estimating Model Parameters
    • 4.1. Two-Input, Two-Output Model
    • 4.2. Two State Model for a Single Heater
    • 4.3. Four State Model
    • 4.4. Assignment: Model Identification
  • 5. Feedback Control
    • 5.1. Relay Control
    • 5.2. Lab Assignment 4: Relay Control
    • 5.3. Lab Assignment: PID Control
    • 5.4. Lab Assignment 4: PI Control
  • 6. State Estimation
    • 6.2. Open and Closed Loop Estimation
  • 7. Optimization
  • 8. Predictive Control and Real Time Optimization
    • 8.1. Simulation, Control, and Estimation using Pyomo
    • 8.2. Simulation, Control, and Estimation using Pyomo

Python Tutorials

  • Python Tutorials
    • Tidy Data and Pandas
    • Coding Controllers with Python Generators
    • Modular Simulation using Python Generators
    • Animation in Jupyter Notebooks
  • Repository
  • Open issue

Index

A | B | M | P | R | S

A

  • Anti-reset-windup

B

  • Bumpless transfer

M

  • MV

P

  • P&ID
  • PID
  • PV

R

  • Reset-windup (also call Integral windup)

S

  • SP

By Jeffrey Kantor and Alexander Dowling

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