Bank of High-Gain Observers in Output Feedback Control: Robustness Analysis Against Measurement Noise

This paper analyzes the output feedback control of a class of unknown nonlinear systems in the presence of measurement noise using multiple high-gain observers (MHGOs). It is well known that single high-gain observers (HGOs) are not able to provide satisfactory performance when the system output is contaminated by noise, and in turn, controllers, which utilize such estimations, perform poorly. To address this issue and improve the control performance, a bank of HGOs is employed, and an appropriate combination of their estimations is used for control purposes. The proposed strategy is capable of mitigating destructive effects of measurement noise and improving transient response, and it does that because it introduces an extra design parameter. The performance recovery capabilities of MHGO-based controllers and the stability of the closed-loop system are discussed. The simulations are performed on an underwater vehicle system and a mechanical system to evaluate the performance of the MHGO-based controller. Furthermore, a detailed comparison to controllers based on conventional HGO, HGO with switching gain, and multi-observer approach is provided, which shows the superiority of the MHGO-based controller over the other methods.