LMI-Based Reset Unknown Input Observer for State Estimation of Linear Uncertain Systems
For control engineers dealing with state estimation under disturbances, this work offers an incremental improvement by applying reset control to unknown input observers.
This paper introduces a Reset Unknown Input Observer (R-UIO) for state estimation of linear uncertain systems, using LMI techniques to reset observer states and improve transient response by decreasing the L2 norm and settling time of estimation error. Simulation results demonstrate the method's efficiency.
This paper proposes a novel kind of Unknown Input Observer (UIO) called Reset Unknown Input Observer (R-UIO) for state estimation of linear systems in the presence of disturbance using Linear Matrix Inequality (LMI) techniques. In R-UIO, the states of the observer are reset to the after-reset value based on an appropriate reset law in order to decrease the $L_2$ norm and settling time of estimation error. It is shown that the application of the reset theory to the UIOs in the LTI framework can significantly improve the transient response of the observer. Moreover, the devised approach can be applied to both SISO and MIMO systems. Furthermore, the stability and convergence analysis of the devised R-UIO is addressed. Finally, the efficiency of the proposed method is demonstrated by simulation results.