The primary goal of this talk is to build a bridge between research on
the Minimum Principle and Dynamic Programming for (deterministic) hybrid
systems, and that on stochastic optimal control theory for classical (i.e.
non-hybrid) systems; this will then yield a unified framework for the
optimal control of deterministic and stochastic hybrid systems. The
secondary goal of the talk is to illustrate the theoretical results for
several analytical and industrial applications, and, in particular, the
application of hybrid optimal control theory for electric vehicles equipped
with multi-stage transmissions.

     In this work deterministic and stochastic hybrid optimal control
problems are studied for systems where autonomous and controlled state
jumps are allowed at the switching instants and, in addition to running
costs, switching between discrete states incurs costs. Features of
special interest in this work are the possibility of state space
dimension change, and existence of low dimensional switching manifolds.

    In addition to analytical examples, an electric vehicle equipped with a
dual-stage planetary transmission is modelled in this framework, where, due
to the special structure of the transmission, the mechanical degree of
freedom changes during the transition period. Hybrid control problems for
energy and time optimality of an electric vehicle acceleration task are
studied which reveal unanticipated aspects of optimal energy saving
strategies for the transmission control.

Location:
Room: EV12.163
Bldg: Concordia University EV Building
1515 St. Catherine Street West
Montreal, Quebec
H3G 2W1