Robust Disturbance Estimation ‐ An Integrated Game Theoretic and Unknown Input Observer Approach

Abstract

This paper presents a new method of disturbance estimation in discrete time invariant linear systems using game theoretic detection filters. First, the direct unknown input observer (UIO) design is reviewed, and its application in disturbance estimation is discussed. Motivated by the UIO design limitations, the game theoretic detection filter is introduced which decouples the multi-variable disturbances into a scalar target disturbance and remaining nuisance disturbances for a virtual plant model. The estimation of the target disturbance is then obtained by the UIO design for the virtual plant. This method can be used to estimate all disturbances in the system individually. Simulation and experimental results from an open loop unstable multi-input-multi-output (MIMO) Active Magnetic Bearing Spindle (AMBS) are presented to demonstrate the robustness of the proposed approach with respect to noises and unmodeled dynamics, and comparison to the direct UIO approach.