Discrete time integral sliding mode control for overhead crane with uncertainties

Xi, Zhiyu; Hesketh, T.

doi:10.1049/iet-cta.2009.0558

Cited by 71 publications

(26 citation statements)

References 12 publications

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“…[21], visual feedback technology is used to achieve the control objective by using two handy cameras. Additionally, sliding mode control strategies are also widely applied to tackle crane system control problems [22][23][24][25]. For example, Almutairi and Zribi [22] achieved the asymptotic stability of the closed-loop overhead crane system by proposing a sliding mode control scheme.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Almutairi and Zribi [22] achieved the asymptotic stability of the closed-loop overhead crane system by proposing a sliding mode control scheme. Xi and Hesketh [23] addressed an integral sliding mode control method for discrete time crane systems with both matched and unmatched uncertainties to ensure the existence of sliding mode in the presence of uncertainties. Based on second-order sliding modes, Bartolin et al [24] guaranteed a fast and precise payload transferring and swing suppression.…”

Section: Introductionmentioning

confidence: 99%

“…Note that in Ref. [23], integral sliding mode control method is proposed by considering perturbations in unactuated dynamics, but it is only designed for discrete-time systems by estimating the present disturbance signal with its past value. Therefore, in order to derive an effective method to achieve crane control in the presence of unknown persistent (even non-vanishing) perturbations in both unactuated and actuated dynamics, this chapter proposes an observer-based robust control method.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust Control of Crane with Perturbations

Wu¹,

Chen²,

Yang³

2018

Adaptive Robust Control Systems

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In the presence of persistent perturbations in both unactuated and actuated dynamics of crane systems, an observer-based robust control method is proposed, which achieves the objective of trolley positioning and cargo swing suppression. By dealing with the unactuated and unknown perturbation as an augmented state variable, the system dynamics are transformed into a quasi-chain-of-integrators form based on which a reduced-order augmented-state observer is established to recover the perturbations appearing in the unactuated dynamics. A novel sliding manifold is constructed to improve the robust performance of the control system, and a linear control law is presented to make the state variables stay on the manifold in the presence of perturbations in unactuated dynamics. A Lyapunov function candidate is constructed, and the entire closed-loop system is proved rigorously to be exponentially stable at the equilibrium point. The effectiveness and robustness of the proposed observer-based robust controller are verified by numerical simulation results.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Control of Crane with Perturbations

Wu¹,

Chen²,

Yang³

2018

Adaptive Robust Control Systems

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“…On the basis of the further research on the technology of computer and graphics, remote sensing technology has been developed rapidly, it plays an increasingly prominent role in the national economic construction and national defense construction. The remote sensing technology is built on the interaction of electromagnetic waves with ground objects, by receiving and processing features of electromagnetic waves reflected or radiated back to obtain ground object information [2] . Satellite remote sensing image target detection is a kind of image interpretation technology, which is based on the characteristics of remote sensing image and combined with the target attribute [3] .…”

Section: Introductionmentioning

confidence: 99%

Satellite Image target Detection Method Based on Multi Agent and Depth Neural Network and Fuzzy Clustering Camera

Liu¹,

Zhou²,

Bao³

2017

Proceedings of the 2nd International Conference on Computer Engineering, Information Science &Amp; Application Technology (ICCI

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Abstract. Remote sensing images are valuable in civil and military applications. In this paper, we propose a remote sensing image target detection method based on a multi-agent system and the deep neural network. The proposed method extracts and fuses the intensity, texture, edges, and the structures in collaboration and parallization, and it provides theoretical and technical supports for real target detection applications.

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“…On the basis of the further research on the technology of computer and graphics [2], remote sensing technology has been developed rapidly, its role in the national economic construction and national defense construction is becoming more and more prominent [3]. The remote sensing technology is built on the interaction of electromagnetic waves with ground objects, by receiving and processing features of electromagnetic waves reflected or radiated back to obtain ground object information.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Image Segmentation Algorithm Based on Multi-agent and Fuzzy Clustering

Liu¹,

Zhou²,

Bao³

2017

dteees

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Abstract. Remote sensing is a technology for monitoring surface information in real time, remote sensing image interpretation has important application value in military and civil fields [1]. In this paper, aiming at the design of remote sensing image segmentation algorithm, we propose a remote sensing image segmentation method based on multi-Agent system and fuzzy clustering. The proposed method extracts and fuses the intensity, texture and edge information in collaboration and penalization, and it provides theoretical and technical support for remote sensing image segmentation.

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Discrete time integral sliding mode control for overhead crane with uncertainties

Cited by 71 publications

References 12 publications

Robust Control of Crane with Perturbations

Robust Control of Crane with Perturbations

Satellite Image target Detection Method Based on Multi Agent and Depth Neural Network and Fuzzy Clustering Camera

Remote Sensing Image Segmentation Algorithm Based on Multi-agent and Fuzzy Clustering

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