Experimental Application of an Augmented Kalman Filter for the State Estimation of an Electro-Hydro Servo-System

Experimental smooth position control of a hydraulic servo motor is the ultimate goal of this paper. The electro-hydro servo-system in this study has two types of nonlinearity as saturation and dead-zone due to the input voltage driver and inherent nonlinear nature of the hydro system respectively. To compensate nonlinearity, control signal apply to the system with a DC bias voltage. Overcoming environmental noise is the major task too. Denoising the system states is the key factor which is realized by an augmented Kalman Filter, since a good performance is not achieved by using standard Kalman filter. In this technique, system states and control signals are estimated simultaneously. Good performance in total system behavior and error reduction in observer’s states is experienced