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.
|Number of pages||6|
|Journal||Proceedings of the IEEE Conference on Decision and Control|
|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