Disturbance attenuation using proportional integral observers

In this paper, we first propose a proportional integral observer design for single-output uncertain linear systems which permit us to attenuate either measurement noise or modelling errors. We show that, when only sensor nois e is present in the system, an integral observer alone su? ces to achieve g ood convergence and filtering properties. On the other hand, when modelling errors and sensor noise are present, we show that, for some classes of lin ear systems, the proportional integral observer allows us to decouple compl etely the modelling uncertainties while keeping satisfactory convergence pr operties. A comparison of the classical proportional observer to the propos ed observers are given via academic simulation examples. We next extend the design to the class of single-output uniformly observable non-linear syste ms. We show through a practical simulation example, dealing with a flexible joint robot, that the non-linear proportional integral has very satisfacto ry disturbance attenuating properties.