<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

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

Slovak University of Technology in Bratislava

Faculty of Mechanical Engineering, Institute of Applied Mechanics and Mechatronics

Strojnícky časopis - Journal of Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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...

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

Online veröffentlicht: 05. Dez. 2019

Seitenbereich: 33 - 44

DOI: https://doi.org/10.2478/scjme-2019-0041

Schlüsselwörter
crane control, analog state vector estimation, analog derivator

© 2019 Grosinger Patrik et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Online veröffentlicht: 05. Dez. 2019

Seitenbereich: 33 - 44

DOI: https://doi.org/10.2478/scjme-2019-0041

Schlüsselwörtercrane control, analog state vector estimation, analog derivator

© 2019 Grosinger Patrik et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
crane control, analog state vector estimation, analog derivator