New results for the design of robust strict positive real systems

The design of filters ensuring convergence of algorithms in the presence of uncertainty in the plant model is a key problem in the area of identification and adaptive control. The authors provide design criteria for filters which yield a family of uncertain discrete time polynomials that are strict positive real over an assigned region of the complex plane. The family of polynomials is defined in terms of its root location region. The results can be applied to the specific problem of determining the frequencies of input harmonics ensuring local convergence of an output error discrete-time identification algorithm where the data are obtained by sampling a continuous-time system