Observer design for large-scale linear systems

This paper presents an approach 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)\times(n-m)
matrix equation, where
n
is the dimension of 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 liner dynamic systems. The resulting observer will have
m
eigenvalues clustered together at a selected point and the remaining
n-2m
eigenvalues are arbitrarily placed.