On the design of integral and proportional integral observers

This paper deals with the design of integral and proportional integral observers for linear uncertain systems. It is shown that, when only sensor noise is present in the system, integral observers permit to achieve good convergence and filtering properties. On the other hand, when modeling errors and sensor noise are present, it is shown that, for some classes of systems, the proportional integral observer allows to decouple completely the modeling uncertainties while keeping satisfactory convergence properties. A comparison of the classical proportional observer to the proposed observers are given via simulation examples.