ACS426   Advanced Control   (10 credits)

Description

Classical control design tends to assume single input single output processes, linear behaviour, no constraints and little uncertainty. In practice of course, real processes are far more complicated. This module explores common scenarios which cause poor behaviour with classical feedback design and then demonstrates how techniques in the popular industrial methods of predictive control are better able to handle these. There is a significant focus on understanding concepts so that students will be competent in how they implement their learning to meet different requirements. Students are encouraged to use software tools to implement predictive control, and classical techniques, on a number of case studies and thus to gain an appreciation of how and which control approach is needed for a variety of different scenarios.

Reading List