Titolo della tesi: Modeling and control of discrete-time and sampled-data port-Hamiltonian systems
Modeling and control of port-Hamiltonian systems are extensively studied in the
continuous-time literature as powerful tools for network modeling and control of complex
physical systems. Since controllers are unavoidably implemented through digital
devices, accurate sampled-data models and control strategies are highly recommended
to prevent a negative impact on the closed-loop performances under digital control.
This thesis contributes to the description of new port-Hamiltonian structures both in
a purely discrete-time and sampled-data framework. Then, on theses bases, stabilizing
and energy-based digital feedback strategies are developed. Regarding modeling,
the proposed state-space forms make use of the concepts of Difference/Differential
Representation (DDR) of discrete-time dynamics and the discrete gradient function.
The proposed models exhibit a Dirac structure that properly defines the storing,
resistive and external elements of the concerned port-Hamiltonian system. For stabilization
purposes, the u-average passivity property has been essential for properly
discussing passivity-based-control (PBC) strategies such as damping output feedback
and Interconnection and Damping Assignment (IDA-PBC) both in discrete time and
under sampling. Three case studies from different physical domains aim to illustrate
the computational aspects related to the modeling and control design and further we
validate their performances by means of simulations.