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Process Control

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Syllabi, schedules, course notes


Process Control: Modeling, Design, and Simulation Process Control: Designing Processes and Control Systems for Dynamic Performance Process Dynamics, Modeling, and Control Chemical Process Control

 Principles and Practice of Automatic Process Control Process Dynamics and Control 



Optimization Software

  • AMPL: A comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems, in discrete or continuous variables.Developed at Bell Laboratories, AMPL lets you use common notation and familiar concepts to formulate optimization models and examine solutions, while the computer manages communication with an appropriate solver. AMPL’s flexibility and convenience render it ideal for rapid prototyping and model development, while its speed and control options make it an especially efficient choice for repeated production runs.
  • APOPT: NLP / MINLP solver for large-scale optimization, available in AMPL, APMonitor, Gekko, MATLAB, Python, and Julia.
  • CasADi: An open-source tool for nonlinear optimization and algorithmic differentiation.
  • Computational Infrastructure for Operations Research (COIN-OR): An initiative to spur the development of open-source software for the operations research community. It provides a list of open-source tools available for operations research and optimization.
  • CONOPT: A solver for large-scale nonlinear optimization (NLP) developed and maintained by ARKI Consulting & Development A/S in Bagsvaerd, Denmark.
  • The General Algebraic Modeling System (GAMS): A high-level modeling system for mathematical programming problems. This site has documentation and related user publications and contributions.
  • Gekko: Optimization software for estimation and predictive control with machine learning and first principles modeling
  • IPOPT: (Interior Point OPTimizer, pronounced eye-pea-Opt) A software package for large-scale nonlinear optimization
  • OPTI Toolbox: A free MATLAB toolbox for constructing and solving linear, nonlinear, continuous, and discrete optimization problems.
  • Pyomo: Python-based, open-source optimization modeling language with a diverse set of optimization capabilities.


Useful links

Educational Resources

Optimization Websites

  • NEOS Guide Website: The NEOS Optimization Guide provides information about the field of optimization and its sub-disciplines. It focuses on the resources available for solving optimization problems, including the solvers available on the NEOS server.
  • ChE Optimization course website – University of Texas at Austin: The course website provides lecture notes, homework materials and solutions for optimization problems that are relevant in Chemical Engineering.
  • Chemical Complex Analysis System: Used to demonstrate optimization of a chemical complex. The System incorporates economic, environmental and sustainable costs and solves a MINLP for the best configuration of plants.
  • Minerals Processing Research Institute: Optimization software and textbook by Prof. Ralph W. Pike, Louisiana State University.
  • Decision Tree for Optimization Software: Has solutions to optimization problems, collection of test results and performance tests, example files ready to use with existing software, softwares which helps formulating an optimization problem or simplifying its solution, and many other helpful materials for optimization.
  • Center for Optimization and Statistical Learning: Optimization Technology Center of Northwestern University and Argonne National Laboratory
  • AlphaOpt: Introduction to optimization (YouTube channel).

Process Systems Research Consortia

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