### Abstract

Original language | English |
---|---|

Pages | 87-98 |

DOIs | |

Publication status | Published - 2006 |

Event | 3rd IFAC Workshop - Nagoya, Japan Duration: 1 Jul 2006 → 1 Jul 2006 |

### Workshop

Workshop | 3rd IFAC Workshop |
---|---|

Country | Japan |

City | Nagoya |

Period | 1/07/06 → 1/07/06 |

### Fingerprint

### Bibliographical note

The full text is not available on the repository.### Cite this

*Direct Discrete-Time Design for Sampled-Data Hamiltonian Control Systems*. 87-98. Paper presented at 3rd IFAC Workshop, Nagoya, Japan. https://doi.org/10.1007/978-3-540-73890-9_6

**Direct Discrete-Time Design for Sampled-Data Hamiltonian Control Systems.** / Laila, Dina Shona; Astolfi, A.

Research output: Contribution to conference › Paper

}

TY - CONF

T1 - Direct Discrete-Time Design for Sampled-Data Hamiltonian Control Systems

AU - Laila, Dina Shona

AU - Astolfi, A.

N1 - The full text is not available on the repository.

PY - 2006

Y1 - 2006

N2 - The success in a model-based direct discrete-time design for nonlinear sampled-data control systems depends on the availability of a good discrete-time plant model to use for the design. Unfortunately, even if the continuous-time model of a plant is known, we cannot in general compute the exact discrete-time model of the plant, since it requires computing an explicit analytic solution of a nonlinear differential equation. One way to solve the problem of finding a good model is by using an approximate model of the plant. A general framework for stabilization of sampled-data nonlinear systems via their approximate discrete-time models was presented in [11]. It is suggested that approximate discrete-time models can be obtained using various numerical algorithms, such as Runge-Kutta and multistep methods. Yet, to the best of the authors knowledge, almost all available results on this direction view the systems as dissipative systems, whereas for design purpose, there are many systems that are better modeled as Hamiltonian conservative systems.

AB - The success in a model-based direct discrete-time design for nonlinear sampled-data control systems depends on the availability of a good discrete-time plant model to use for the design. Unfortunately, even if the continuous-time model of a plant is known, we cannot in general compute the exact discrete-time model of the plant, since it requires computing an explicit analytic solution of a nonlinear differential equation. One way to solve the problem of finding a good model is by using an approximate model of the plant. A general framework for stabilization of sampled-data nonlinear systems via their approximate discrete-time models was presented in [11]. It is suggested that approximate discrete-time models can be obtained using various numerical algorithms, such as Runge-Kutta and multistep methods. Yet, to the best of the authors knowledge, almost all available results on this direction view the systems as dissipative systems, whereas for design purpose, there are many systems that are better modeled as Hamiltonian conservative systems.

U2 - 10.1007/978-3-540-73890-9_6

DO - 10.1007/978-3-540-73890-9_6

M3 - Paper

SP - 87

EP - 98

ER -