Advanced Process Operations - CENG97007
This advanced course provides the student with the ability to formulate, solve and
interpret meaningful optimization problems embedding dynamic systems, with
applications to batch process optimization, optimal transition in continuous process, and
dynamic parameter esti-mation. Emphasis is placed on understanding conditions for
optimality as well as commonly available solution techniques. Software packages are used
for solving realistic engineering problems. The course consists of a combination of lectures
and practical work.
By the end of the course, the students should be able to:
• Recognize opportunities for dynamic optimization, and translate them into
mathematical models. This involves selecting the right model complexity and formulating
meaningful objective functions and constraints for problems in optimal control (batch
processes, process start-up, change-over or shutdown, etc), as well as for parameter
estimation and optimal experimental design in dynamic models.
• Solve dynamic optimization problems using state-of-the-art methods and tools
(gPROMS, GAMS). This includes an awareness of numerical solution methods of dynamic
optimiza-tion as well as dynamic sensitivity analysis.
• Analyze dynamic optimization problems and explain the optimal solutions in terms
of their structure (control arcs, active constraints). This requires familiarity with conditions
for optimality, including singular and path-constrained problems.
Process Model Solution and Optimisation - CENG96011
The aim of this course is to introduce the students to advanced numerical methods for the solution and optimisation of both linear and nonlinear systems, so that they are able to apply them in real chemical engineering problems. The students will learn about optimisation theory. They will also learn how to formulate optimisation models for linear and nonlinear problems, select an appropriate solution method, and compute a numerical solution. The numerical software tools are Matlab and GAMS.