Stability, control and reliability of a ship crane payload motion

Yurchenko, Daniil; Alevras, Panagiotis

doi:10.1016/j.probengmech.2014.10.003

Cited by 28 publications

(13 citation statements)

References 22 publications

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“…While it is common to state the design objectives or constraints in a RDO sense, stating them to get reliability (RBDO) and actively using them in the optimisation process is less common. However, they are quite useful, since they provide a deeper (more reliable) insight on controller performance, its risk of failures and its expected behaviour [Alfi et al, 2015, Yurchenko and Alevras, 2014, Moberg et al, 2009, Stengel and Marrison, 1992].…”

Section: Xil Platforms Within a Mood Framework For Controller Tuning mentioning

confidence: 99%

Enhancing controller’s tuning reliability with multi-objective optimisation: From Model in the loop to Hardware in the loop

Carrau

Reynoso-Meza

García-Nieto

et al. 2017

Engineering Applications of Artificial Intelligence

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In general, the starting point for the complex task of designing a robust and efficient control system is the use of nominal models that allow to establish a first set of parameters for the selected control scheme. Once the initial stage of design is achieved, control engineers face the difficult task of Fine-Tuning for a more realistic environment, where the environment conditions are as similar as possible to the real system. For this reason, in the last decades the use of Hardware-in-The-Loop (HiL) systems has been introduced. This simulation technique guarantees realistic simulation environments to test the designs but without danger of damaging the equipment. Also, in this iterative process of Fine-Tuning, it is usual to use different (generally conflicting/opposed) criteria that take into account the sensitivities that always appear in every project, such as economic, security, robustness, performance, for example. In this frame-*

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Section: Xil Platforms Within a Mood Framework For Controller Tuning mentioning

confidence: 99%

Enhancing controller’s tuning reliability with multi-objective optimisation: From Model in the loop to Hardware in the loop

Carrau

Reynoso-Meza

García-Nieto

et al. 2017

Engineering Applications of Artificial Intelligence

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show abstract

“…Ghigliazzaa and Holmes [16] considered the dynamics of a spherical pendulum with a moving support, studying the payload motion of a tower crane under linear acceleration and moving on a circular support. With a similar application in mind, the dynamics of a spherical pendulum under stochastic excitation and the first passage problem was studied in [17]. Perig et al concentrated on small oscillations of a spherical pendulum with a uniformly rotating suspension center for modeling slewing crane motion [18].…”

Section: Introductionmentioning

confidence: 99%

Dynamic response of the spherical pendulum subjected to horizontal Lissajous excitation

et al. 2020

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This paper examines the oscillations of a spherical pendulum with horizontal Lissajous excitation. The pendulum has two degrees of freedom: a rotational angle defined in the horizontal plane and an inclination angle defined by the pendulum with respect to the vertical z axis. The results of numerical simulations are illustrated with the mathematical model in the form of multi-colored maps of the largest Lyapunov exponent. The graphical images of geometrical structures of the attractors placed on Poincaré cross sections are shown against the maps of the resolution density of the trajectory points passing through a control plane. Drawn for a steady-state, the graphical images of the trajectory of a tip mass are shown in a three-dimensional space. The obtained trajectories of the moving tip mass are referred to a constructed bifurcation diagram.

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“…In many published works, several position and antiswing control algorithms of gantry crane have been proposed and implemented. A model predictive control in [6]Fuzzy control in [7], combination of NCTF and Fuzzy logic control in [2], backstepping controller proposed in [8], linear quadratic regulator control in [9], PID controller in [10], bang-bang controller in [11], feedback and input shaping approach in [12], genetic algorithm technique in [13], wireless microelectromechanical system is proposed in [14] and Firefly Algorithm (FA) in [15]. In the work of [16], an optimal control scheme with LQR are implemented for prompt suppression of the load swing and accurate crane positioning in spite of large initial swing and collision.…”

Section: Introductionmentioning

confidence: 99%

Vision Based Control of Gantry Crane System

Okubanjo¹,

Oyetola²,

Adekomaya³

2018

Anadolu University Journal of Science and Technology-a Applied Sciences and Engineering

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Heavy materials handling requires a sophisticated tool for efficient and optimum operations. In recent times, gantry cranes are considered as a dependable choice in terms of handling capacity, effectiveness, timeliness and safety. However, positioning of a trolley to the desired set point as fast as possible within minimum time without overshoot and payload induced oscillation have remained obstacles in crane dynamic control. Several control algorithms have been proposed, tested and implemented based on classical control. Recently, vision control has been introduced in the field of mechatronics as a bridging gap with little or no impact. In this paper, a vision based software control model is proposed such that webcam serves as a capturing sensor and the National Instrument LabVIEW is used as a programming tool for both image processing and crane control. Subsequently, the results of the proposed algorithm are experimentally validated by step increase in the trolley position. According to the results analysis, it is evident that the webcam performance is at an optimum level when compared with the installed sensor in positioning the trolley and minimizing the payload oscillation.

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Stability, control and reliability of a ship crane payload motion

Cited by 28 publications

References 22 publications

Enhancing controller’s tuning reliability with multi-objective optimisation: From Model in the loop to Hardware in the loop

Enhancing controller’s tuning reliability with multi-objective optimisation: From Model in the loop to Hardware in the loop

Dynamic response of the spherical pendulum subjected to horizontal Lissajous excitation

Vision Based Control of Gantry Crane System

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