Application of Analogue Derivators for Obtaining Direct Non-Measurable Components of the State Vector in Crane Control

This paper presents a simple-to-use system for estimating non-measurable components of crane state vector considering parameter changes. To obtain them, it is possible to use a numerical derivative, where the measurement noise causes great inaccuracies, or the Luenberger observer and Kalman filter, which require knowledge of the dynamics of the controlled system, which is constantly changing with the crane.