Optimal Stochastic Observers Applied to Hydraulic Actuation Systems

The states and parameters of a hydraulic actuation system are estimated given measurement information from available sensors. A linear simulation is utilized and a stochastic model is generated by incorporating modeling errors, tolerances, and other random errors. A linear measurement model is assumed with additive white Gaussian noise contaminating the measurement data. A Kalman/Bucy type filtering algorithm is utilized to estimate the states and parameters of the hydraulic system at hand. A brief discussion indicating the use of these estimates for failure detection or performance enhancement is included, with direct reference to redundancy management and backup provision. Simulation results are plotted in various diagrams indicating the performance of the estimator.