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

<p>This work introduces the foundation of a new class of input shaping algorithm, designed based on the particle swarm optimisation. This algorithm is utilised to control the residual vibrations in the crane system. The motivation is the development of simple algorithms and architecture for controlling the motion in under-actuated nonlinear systems with minimal modelling effort. By recording the payload swing signal of the crane only once, the approach can automatically calculate the optimisation amplitude and time locations of the impulses required by a common zero-vibration-derivative (ZVD) technique. In this work, we use this algorithm to design a ZVD shaper for controlling the motion of an under-actuated nonlinear crane model system. We validate the approach using experiments. If this algorithm is implanted into the embedded system and applied to the actual crane, which will solve the problem of the traditional ZVD parameter adjustment and improve the vibration suppression effect of the ZVD Algorithm.</p>
</abstract>

This work introduces the foundation of a new class of input shaping algorithm, designed based on the particle swarm optimisation. This algorithm is utilised to control the residual vibrations in the crane system. The motivation is the development of simple algorithms and architecture for controlling the motion in under-actuated nonlinear systems with minimal modelling effort. By recording the payload swing signal of the crane only once, the approach can automatically calculate the optimisation amplitude and time locations of the impulses required by a common zero-vibration-derivative (ZVD) technique. In this work, we use this algorithm to design a ZVD shaper for controlling the motion of an under-actuated nonlinear crane model system. We validate the approach using experiments. If this algorithm is implanted into the embedded system and applied to the actual crane, which will solve the problem of the traditional ZVD parameter adjustment and improve the vibration suppression effect of the ZVD Algorithm.

Automatic parameter selection ZVD shaping algorithm for crane vibration suppression based on particle swarm optimisation

College of Mechanical and Electrical Engineering

Beijing Information Science and Technology University

Department of Computer Science, Faculty of Computing and Information Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This work introduces the foundation of a new class of input shaping algorithm, designed based on the particle swarm optimisation. This algorithm is utilised to...

Number	parameter	Value
1		0.6
2	wc₁	2
3	c₂	2
4	Dimension	2
5	η₁	1
6	η₂	1

No.	Pendulum length (mm)	Damping percentage (%)	Peak swing angle (°)	Adjusting time (s)
1	14.5	89.85	5.63	1.90
2	15.5	86.87	5.889	1.72
3	12.5	62.46	7.56	2.26

Automatic parameter selection ZVD shaping algorithm for crane vibration suppression based on particle swarm optimisation

Published Online: Dec 15, 2021

Page range: 73 - 82

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00075

Keywords
Crane, Vibration suppression, Zero-vibration-derivative, Particle swarm optimisation

© 2021 Bo Xu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

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Fig. 8

Initial parameters of PSO

Vibration suppression effect

Automatic parameter selection ZVD shaping algorithm for crane vibration suppression based on particle swarm optimisation

Published Online: Dec 15, 2021

Page range: 73 - 82

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00075

KeywordsCrane, Vibration suppression, Zero-vibration-derivative, Particle swarm optimisation

© 2021 Bo Xu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Initial parameters of PSO

Vibration suppression effect

Keywords
Crane, Vibration suppression, Zero-vibration-derivative, Particle swarm optimisation