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 matrix equation, where is the dimension of state and 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 eigenvalues clustered together at a selected point and the remaining eigenvalues are arbitrarily placed.