Damped One-Mode Vibration Model State and Parameter Estimation via Pre-Filtered Moving Horizon Observer

The estimation of parameters and states is one of the core data-processing algorithms used for the monitoring and control of continuum or structured mechatronical systems (e.g., flexible robotic arms and cantilevers). The measurements taken from the sensors combined with an appropriate model can filter the states and extract information about vibration dynamics parameters such as damping and spring constants. This paper presents a method based on the application of a Moving Horizon Observer (MHO) for state and parameter estimation of a lightly-damped vibrating system. A numerical experiment on a single-degree-of-freedom (SDOF) system is performed to demonstrate the method on noisy measurements and to compare the MHO with the benchmark Extended Kalman Filter (EKF). Test scenarios show that the MHO appears to be more robust with respect to modeling errors.