## Abstract

An approach is presented which reduces the computational requirements in observer design. Specifically, a procedure is developed which reduces the observer design to an algebraic problem of solving an (n-2m) multiplied by (n-m) matrix equation, where n is the dimension of the state and m is the dimension of the output. It is also shown that for a special class of problems, which appears very often in time-series modeling, the computational requirements can be much further reduced. The procedure developed in this paper is applicable to both discrete-time and continuous-time linear dynamic systems. The resulting observer will have m eigenvalues clustered together at a selected point and the remaining n-2m eigenvalues are arbitrarily placed.

Original language | English |
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Pages (from-to) | 675-680 |

Number of pages | 6 |

Journal | Proceedings of the IEEE Conference on Decision and Control |

DOIs | |

State | Published - 1978 |

Event | Proc IEEE Conf Decis Control Incl Symp Adapt Processes 17th - San Diego, CA, USA Duration: 10 Jan 1979 → 12 Jan 1979 |