## Abstract

The observer-Kalman filter/eigensystem realisation algorithm is applied to the problem of generating a minimal state-space model realisation from a nonlinear helicopter model. The paper presents an interim result using a 10th order linear model, discusses the implications of this and generates some general guidelines before applying the technique to a nonlinear model. The outcome is a linear realisation which gives a better representation of the nonlinear model than obtained using small perturbation linearisation methods. The technique is capable of extracting unstable plant models from closed-loop stabilised systems, even when the feedback dynamics are not known.

Original language | English |
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Pages (from-to) | 415-422 |

Number of pages | 8 |

Journal | IEE-Proceedings-Control-Theory-and-Applications |

Volume | 145 |

Issue number | 4 |

Publication status | Published - Jul 1998 |

## Keywords

- helicopter identification
- eigensystem realisation algorithm
- nonlinear systems
- SYSTEM-IDENTIFICATION
- OBSERVER