A novel unknown-input estimator for disturbance estimation and compensation

Abstract

A novel unknown-input estimator (UIE) for estimating and rejecting disturbances is proposed in this paper. Effective treatment of unknown disturbing inputs is of vital importance to maintaining satisfactory performance of control systems. Advanced methods that estimate these disturbances and cancel them accordingly outperform traditional approaches. However, limitations remain, including requirements for some knowledge on unknown inputs, derivatives of measured outputs, inversion of plant dynamics, constrained state observer design, parameter optimisation (global optimum not guaranteed), or complicated structures. The proposed UIE is exempted from the aforementioned limitations. It consists of an estimation gain matrix, a state observer, and a low-pass-filter-characterised subsystem. Comparison via simulation is drawn between the new UIE and a benchmark disturbance observer on a multi-input multi-output system. The proposed UIE is shown to be more effective in estimating and compensating unknown inputs.