With respect to the future urban mobility, modern electrical bicycles,
advanced motorcycles and innovative two-wheeled vehicles are arresting
enormous amount of attention. Especially, model-based control and
optimal trajectory planning for such vehicles are important to the
research and development of the future. Therefore, a reliable and yet
usable vehicle model as well as a systematic approach to motion control
for two-wheeled vehicles are essential, to which this work makes a
contribution. Currently available two-wheeled vehicle models are mostly
either too complex to be used for a systematic control synthesis, or too
simple such that the physical behaviour of the vehicle is no more
represented. In this thesis, a unifying approach to modelling and
control for autonomous two-wheeled vehicles is presented. The resulting
model is generally valid and physically detailed enough to represent the
characteristic dynamical behaviour such as the self-stability. At the
same time, it is suited to a systematic control synthesis. Furthermore,
the systematic extenddability, for instance by a rider, is demonstrated.
The model is validated by simulations and by comparison to well-known
models from the literature. The proposed vehicle model is derived in the
Lagrangian and Hamiltonian framework and used for model-based optimal
trajectory planning. Furthermore, a passivity-based trajectory tracking
controller is designed based on the resulting port-Hamiltonian system
using the so-called generalised canonical transformations. Such a
controller is physically interpretable and robust against parameter
uncertainties. To this end, existing approaches of passivity-based
controller design are extended and adjusted for two-wheeled vehicles.
Finally, a prototype two-wheeled vehicle is introduced which is used for
experimental validation of the model and to demonstrate motion control
algorithms for autonomous two-wheeled vehicles.
