Distributed-mass payload dynamics and control of dual cranes undergoing planar motions

Zhao, Xiao; Huang, Jie

doi:10.1016/j.ymssp.2019.02.032

Cited by 33 publications

(16 citation statements)

References 31 publications

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“…The EI shaper has an advantage over the ZVD and ZV shapers that it has the same impulse duration as that of ZVD but is more insensitive to parameter variation. 29,30 The shaper has been implemented for vibration reduction of various flexible systems and has been shown to provide a higher robustness when compared with the ZV and ZVD shapers. 31…”

Section: Input Shaper Designmentioning

confidence: 99%

Payload swing control of a tower crane using a neural network–based input shaper

Fasih

Mohamed

Husain

et al. 2020

Measurement and Control

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This paper proposes an input shaping technique for efficient payload swing control of a tower crane with cable length variations. Artificial neural network is utilized to design a zero vibration derivative shaper that can be updated according to different cable lengths as the natural frequency and damping ratio of the system changes. Unlike the conventional input shapers that are designed based on a fixed frequency, the proposed technique can predict and update the optimal shaper parameters according to the new cable length and natural frequency. Performance of the proposed technique is evaluated by conducting experiments on a laboratory tower crane with cable length variations and under simultaneous tangential and radial crane motions. The shaper is shown to be robust and provides low payload oscillation with up to 40% variations in the natural frequency. With a 40% decrease in the natural frequency, the superiority of the artificial neural network–zero vibration derivative shaper is confirmed by achieving at least a 50% reduction in the overall and residual payload oscillations when compared to the robust zero vibration derivative and extra insensitive shapers designed based on the average operating frequency. It is envisaged that the proposed shaper can be further utilized for control of tower cranes with more parameter uncertainties.

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Section: Input Shaper Designmentioning

confidence: 99%

Payload swing control of a tower crane using a neural network–based input shaper

Fasih

Mohamed

Husain

et al. 2020

Measurement and Control

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“…Transfer matrix is calculated using MATLAB and elements of the Eq. (7), (8) and (9) are drawn from matrix.…”

Section: Replacement Of the Cars Is Symbolised With X1 X2 And X3mentioning

confidence: 99%

“…Based on that, a nonlinear control strategy is proposed. Zhao and Huang [8] develop a new method to predict the natural frequency of dual planar cranes with different cable lengths. Smoczek [9] presents the fuzzy logic-based robust feedback anti-sway control system which can be applicable either with or without a sensor of sway angle of a payload.…”

Section: ⅰ Introductionmentioning

confidence: 99%

Sway Control of 3-Cars Crane System Using Proposed Fuzzy-PID Controller

Yıldırım¹

2020

RIiM

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This paper presents a novel control approach for 3 cars crane systems. Nowadays; some problems for carrying unpredicted loads of crane systems exist. On the other hand; long bar loads are very important to carry without touch on other materials in factories. In this simulation study, fuzzy based controllers were designed to control vibrations of 3 cars crane system. The simulation results are improved and show this kind of controllers will be employed in real time such systems.

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“…[9][10][11][12] However, few studies have been focused on multiple cranes moving a large payload. Some research works reported the dynamic model of dual cranes carrying a huge payload undergoing planar motions, [13][14][15] in which the dynamic model includes the payload swing and pitch. However, little literature presented threedimensional dynamics of this system.…”

Section: Introductionmentioning

confidence: 99%

Dynamics and control of three-dimensional dual cranes transporting a bulky payload

Huang

Zhu

2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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The inevitable oscillations of the payload decrease the positioning accuracy and lessen the safety in dual cranes carrying a large payload. In the presence of the structural flexibility, the dynamics of dual cranes are governed by the payload swing, pitch, and twisting after considering three-dimensional motions. However, little research has been directed at the modeling and control of three-dimensional dual cranes. A dynamic model of three-dimensional dual cranes including the payload swing, pitch and twisting is described. Moreover, a combined modified extra-insensitive input shaper and four-pieces smoother method is proposed to control the swing, pitch, and twisting of the payload. The dynamic behavior of the nonlinear model and the effectiveness of the new control method are verified experimentally on dual cranes carrying a slender beam.

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Distributed-mass payload dynamics and control of dual cranes undergoing planar motions

Cited by 33 publications

References 31 publications

Payload swing control of a tower crane using a neural network–based input shaper

Payload swing control of a tower crane using a neural network–based input shaper

Sway Control of 3-Cars Crane System Using Proposed Fuzzy-PID Controller

Dynamics and control of three-dimensional dual cranes transporting a bulky payload

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