Uncertain parameter estimation for a class of nonlinear systems using a polynomial representation of outputs

A novel approach to estimation of structured uncertainties is proposed for a class of nonlinear systems based on algebraic geometry tools. The notion of Polynomial Partition of Unity (PPU) is introduced and it constitutes a key feature of the proposed estimation technique, whose main advantage is the potentiality of being executed offline. Provided that the system dynamics satisfy some PPU and gradient properties, and collecting a sufficient number of measurements at different time steps, the values of unknown parameters are proved to be included in the finite set of common solutions to a family of polynomial equations. An optimization method based on multiple-models is then proposed to further refine the estimation. The case-study of sensorless permanent magnet synchronous motors is presented as a support to theoretical developments.