This letter deals with interconnection and damping assignment for discrete-time port-Hamiltonian systems. Based on a novel state representation, suitably shaped to address energy-based control design, the nonlinear discrete-time controller is characterized and the solution is explicitly computed in the linear case. The design worked out on the exact sampled-data model of a mechanical system confirms the effectiveness of the controller.

The paper deals with stabilization of feedforwardmultiple cascade dynamics under sampling. It is shown that u-average passivity concepts and Lyapunov methods can be profitably exploited to provide a systematic sampled-data design procedure. The proposed methodology recalls the continuous-time feedforwarding steps and can be applied under the same assumptions as those set over the continuous-time cascade dynamics. The final sampled feedback is carried out through a three steps procedure that involves iterative passivation and stabilization in the u-average sense. Constructive aspects are developed to compute approximate solutions which are indeed implemented in practice. An example is worked out with comparative simulations with respect to usual sampled-and-hold implementations.

This article investigates the transformation of Hamiltonian structures under sampling. It is shown that the exact sampled equivalent model associated to a given port-Hamiltonian continuous-time dynamics exhibits a discrete-time representation in terms of the discrete gradient, with the same energy function but modified damping and interconnection matrices. By construction, the proposed sampled-data dynamics guarantees exact matching of both the state evolutions and the energy-balance at all sampling instants. Its generalization to port-controlled Hamiltonian dynamics leads to characterize a new power conjugate output so recovering the concept of average passivation. On these bases, energy-management control strategies can be proposed. An energetic interpretation of the approach is confirmed by its formulation in the Dirac formalism. Two classical examples are worked out to validate the proposed sampled-data modeling in a comparative way with the literature.

This article discusses the Dirac structure and the state-space representation of a class of port-Hamiltonian systems that evolve in discrete time. The characterization of the underlying Dirac structure depends on separating the stored energy associated with the system into two distinct components. Moreover, it is shown that power-preserving interconnection and negative output feedback maintain the port-Hamiltonian structure while increasing the dimension of the Dirac structure. Finally, the proposed approach is illustrated by means of an approximated gravity pendulum model.