|Both academia and industry have recently directed a considerable amount of
research effort on hybrid systems. Hybrid systems typically arise when
continuous plants are coupled with controllers that involve discrete logic
actions. Although hybrid systems are encountered in many practical situations,
up to now most controllers for such systems are designed using ad hoc and
heuristic procedures. Due to the complex nature of hybrid systems, it is
infeasible to come up with generally applicable control design methods.
In this project we focus on structured control design methods
for specific classes of hybrid systems that are industrially relevant. These
methods will be extensions of the model predictive control (MPC) framework for
continuous systems, so as to include hybrid systems. The MPC scheme is
nowadays very popular in the oil refining and (petrochemical) process industry
and has adequately proved its usefulness in practice. MPC offers attractive
features that makes this control approach also interesting and relevant for
extension to hybrid systems.
In this project we will develop high performance MPC controller design techniques
for hybrid systems.
Currently, we have already obtained some initial results on MPC for special subclasses
of hybrid systems, viz. piecewise-affine systems and
max-plus linear systems. In this project we keep on
extending these results to other relevant classes
of hybrid systems, and we thoroughly investigate and formalize the design process,
improve optimization procedures to realize real-time implementation, and use
the results for practical problems of the partners from industry.