Payload twisting dynamics and oscillation suppression of tower cranes during slewing motions

Peng, Jiaohui; Huang, Jie; Singhose, William

doi:10.1007/s11071-019-05247-4

Cited by 52 publications

(19 citation statements)

References 24 publications

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“…Additionally, the FP smoother reveals low-pass filtering effect for suppressing the third-mode frequency. Note that the FP smoother provides more robustness than previously presented smoothers, such as the two-pieces smoother 24 and three-pieces smoother. 25…”

Section: Oscillation Suppressionmentioning

confidence: 94%

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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Section: Oscillation Suppressionmentioning

confidence: 94%

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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“…It is noted from Table 1 that for both ZVD shapers, A 2 has the same magnitude for all lengths and since DT 2 is multiple of DT 1 , the ANN was used to generate three parameters for each ZVD shaper which are A 1 , A 3 and DT 1 to reduce the computational time and to improve its performance. The weights of neurons between hidden layer and input layer w j, 1 are shown in equation (18), whereas equation (19) shows the weights for w 1, j and w 6, j as examples extracted from w k, j . Table 2 shows the bias values of the hidden and output neurons, obtained through ANN training data in Table 1.…”

Section: Ann-based Zvd Shapermentioning

confidence: 99%

“…These include input shaping, 13,14 filters 15 and command smoothing. [16][17][18] As reported in the review paper, 1 a large number of publications focused on design and implementation of the feedforward strategies on gantry and overhead cranes as compared to the tower and rotary cranes. In contrast to the gantry and overhead cranes, the effects of nonlinearities in a tower crane are more substantial due to the rotational motion.…”

Section: Introductionmentioning

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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“…Several smoothing techniques showed successful results such as the S-curve (Eloundou and Singhose, 2002), the Gaussian (Ramli et al, 2017), the trigonometric transition function (Masoud and Alhazza, 2017; Vaughan et al, 2010), the spline function (Alhazza and Masoud, 2010) and the cam polynomial (Huang et al, 2015). Recent work (Peng et al, 2019) used an open-loop control method with command smoothing to reduce both the swinging and twisting of the payloads during slewing motions in tower cranes. However, smooth commands suffer from increasing rise-time and slow system motion (Alhazza et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

A smooth optimized input shaping method for two-dimensional crane systems using Bezier curves

Alfadhli

Khorshid

2021

Transactions of the Institute of Measurement and Control

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Conventional input shaping commands have been successfully employed to suppress residual vibration in the payload rest-to-rest transportation process. Most of these methods introduce an impractical large and sudden variation on the acceleration profile. This paper presents a new smooth command input with adjustable time length and limited jerks. The command input is generated from the trolley displacement using a Bezier curve function by adjusting the position of the control points, which were divided into boundary and intermedium points. The boundary control points are selected to accurately move the trolley to its desired position with zero velocity and acceleration at the closing motion. The positions of the intermedium points were optimized using a particle swarm scheme for reducing maneuvering time while suppressing the payload oscillations at the end of the process and satisfying physical system constraints. Several cases were discussed for fixed cable length, variable cable involving single and multi-hoisting mechanisms, and different maneuver times. Simulated results were validated experimentally on a laboratory size crane. The results demonstrated that the proposed input Bezier-curve shaper provides an effective, reliable, and practical technique to be used for the payload transportation process. Moreover, the proposed method can generate asymmetrical acceleration and deceleration motions, which cannot be achieved using existing smoother commands.

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Payload twisting dynamics and oscillation suppression of tower cranes during slewing motions

Cited by 52 publications

References 24 publications

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

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

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

A smooth optimized input shaping method for two-dimensional crane systems using Bezier curves

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