Partial Feedback Linearization Control of the three dimensional overhead crane

Tuấn, Lê Anh; Kim, Gook-Hwan; Lee, Soon-Geul

doi:10.1109/coase.2012.6386314

Cited by 24 publications

(21 citation statements)

References 19 publications

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“…The solution to track desired trajectory of trolley and anti-sway of load are particular characteristics of overhead crane. The approaches for anti-sway are based on PD techniques control [1], partial feedback linearization control [2,3], nonlinear control [4 -11], robustadaptive control [12 -14], fuzzy -neural network controller [15,16]. The above controllers are often used for uncertainly parameters of overhead crane and when executed to combine with two loop circuits : the adaptive parameters adjustment loop and control loop.…”

Section: Problem Statementmentioning

confidence: 99%

High Order Sliding Mode Control With Anti-Sway Based Compensation on Artificial Neural Network by Pso Algorithm for Overhead Crane

Hai

Thai

Nga

et al. 2017

Journal of Science and Technology

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This paper proposes a second order sliding mode controller combined with signal set calibrator for overhead crane tracking desired position and resisting disturbance. High order sliding mode controller ensures that the overhead crane tracks desired trajectory and resists disturbance. Neural network is trained by particle swarm optimization algorithm (PSO) to compensate anti-sway for load. The results on the computer simulation show that high order sliding mode controller with anti-sway compensation for overhead crane tracks desired trajectory and the swing of load that is smaller than high order sliding mode controller without anti-sway compensation.

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Section: Problem Statementmentioning

confidence: 99%

High Order Sliding Mode Control With Anti-Sway Based Compensation on Artificial Neural Network by Pso Algorithm for Overhead Crane

Hai

Thai

Nga

et al. 2017

Journal of Science and Technology

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“…Bechlioulis and Rovithakis [8] developed a multiple-input, multiple-output tracking controller with adaptive feedback linearisation and Shojaei et al [9] demonstrated the ability of adaptive feedback linearisation in aiding effective trajectory tracking in the presence of both parametric and nonparametric uncertainties in wheeled robots. Tuan et al [10] designed a controller based on partial feedback linearisation of the nonlinear dynamics of a 3D overhead crane.…”

Section: Shock and Vibrationmentioning

confidence: 99%

Feedback Linearisation for Nonlinear Vibration Problems

Jiffri

Paoletti

Cooper³

et al. 2014

Shock and Vibration

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Feedback linearisation is a well-known technique in the controls community but has not been widely taken up in the vibrations community. It has the advantage of linearising nonlinear system models, thereby enabling the avoidance of the complicated mathematics associated with nonlinear problems. A particular and common class of problems is considered, where the nonlinearity is present in a system parameter and a formulation in terms of the usual second-order matrix differential equation is presented. The classical texts all cast the feedback linearisation problem in first-order form, requiring repeated differentiation of the output, usually presented in the Lie algebra notation. This becomes unnecessary when using second-order matrix equations of the problem class considered herein. Analysis is presented for the general multidegree of freedom system for those cases when a full set of sensors and actuators is available at every degree of freedom and when the number of sensors and actuators is fewer than the number of degrees of freedom. Adaptive feedback linearisation is used to address the problem of nonlinearity that is not known precisely. The theory is illustrated by means of a three-degree-of-freedom nonlinear aeroelastic model, with results demonstrating the effectiveness of the method in suppressing flutter.

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“…Fulfilling this gap, Park et al propose a feedback linearization for trolley and hoisting operations to guarantee asymptotic stability. Similarly, a partial feedback control is developed in [8]; the control is a linear combination of feedback linearization from actuated and unactuated dynamics. Subsequently, the closed-loop system is proven to be asymptotically stable.…”

Section: Introductionmentioning

confidence: 99%

Vibration Suppression Control of a Flexible Gantry Crane System with Varying Rope Length

Nguyễn

Hieu

Quang

2019

Journal of Control Science and Engineering

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The paper presents a control approach to a flexible gantry crane system. From Hamilton’s extended principle the equations of motion that characterized coupled transverse-transverse motions with varying rope length of the gantry is obtained. The equations of motion consist of a system of ordinary and partial differential equations. Lyapunov’s direct method is used to derive the control located at the trolley end that can precisely position the gantry payload and minimize vibrations. The designed control is verified through extensive numerical simulations.

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Partial Feedback Linearization Control of the three dimensional overhead crane

Cited by 24 publications

References 19 publications

High Order Sliding Mode Control With Anti-Sway Based Compensation on Artificial Neural Network by Pso Algorithm for Overhead Crane

High Order Sliding Mode Control With Anti-Sway Based Compensation on Artificial Neural Network by Pso Algorithm for Overhead Crane

Feedback Linearisation for Nonlinear Vibration Problems

Vibration Suppression Control of a Flexible Gantry Crane System with Varying Rope Length

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