MSc Advanced Control and Systems Engineering / Course details

Part A: Process Control

• PID controller structure: ideal/parallel/series, position/velocity implementation of digital PID.
• PID controller tuning: Ziegler-Nichols and Cohen-Coon, Internal Model Control with lambda-tuning.
• Enhanced control: cascade control, feedforward control, multi-loop control utilising de-couplers, Smith Predictor.
• Multi-loop interaction analysis using Relative Gain Array.
• Real-time process optimisation using Linear Programming technique.

Part B: Model Predictive Control (MPC)

• MPC control formulation: simple unconstrained optimal control formulation, general characteristics of MPC formulation, translation of MPC problem into quadratic programming optimisation problem, constant output disturbance observer model, infeasibility and softening of the constraints.
• Practical MPC implementation considerations: empirical model development, usage of design/tuning parameters, implementation/commissioning of MPC.
• Design of MPC control for typical CSTR chemical reactor as well as distillation column.

1. Introduce students to the fundamental concepts of applied industrial process control, including cascade and feedforward control structures as well as the use of de-couplers.

2. Introduce students to the formulation and the main implementation details regarding Model Predictive Control (MPC) as well as the real-time process optimisation.

This unit is taught during 6-week period during which several 3-hour lectures take place every week and two 3-hour lab sessions are scheduled to take place during the 6-week period.