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Research Papers

Direct Adaptive Fuzzy Moving Sliding Mode Proportional Integral Tracking Control of a Three-Dimensional Overhead Crane

[+] Author and Article Information
Tsung-Chih Lin

Department of Electronic Engineering,
Feng-Chia University,
Taichung 40724, Taiwan
e-mail: tclin@fcu.edu.tw

Yu-Chen Lin

Department of Automatic Control Engineering,
Feng-Chia University,
Taichung 40724, Taiwan
e-mail: yuchlin@fcu.edu.tw

Majid Moradi Zirkohi

Department of Electrical Engineering,
Behbahan Khatam Alanbia
University of Technology,
Behbahan 63616-47189, Iran
e-mail: majid.moradi.z@gmail.com

Hsi-Chun Huang

Department of Electronic Engineering,
Feng-Chia University,
Taichung 40724, Taiwan
e-mail: louishya14@gmail.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received October 9, 2015; final manuscript received April 6, 2016; published online June 8, 2016. Assoc. Editor: Heikki Handroos.

J. Dyn. Sys., Meas., Control 138(10), 101001 (Jun 08, 2016) (11 pages) Paper No: DS-15-1504; doi: 10.1115/1.4033414 History: Received October 09, 2015; Revised April 06, 2016

In this paper, a novel direct adaptive fuzzy moving sliding mode proportional integral (PI) tracking control of a three-dimensional (3D) overhead crane which is modeled by five highly nonlinear second-order ordinary differential equations is proposed. The fast and robust position regulation and antiswing control can be achieved based on the proposed approach. Due to universal approximation theorem, fuzzy control provides nonlinear controller, i.e., fuzzy logic controllers, to perform the unknown nonlinear control actions. Simultaneously, in order to achieve fast and robust regulation and to enhance robustness in the presence of disturbance and parameter variations, moving sliding mode control (SMC) is introduced to tradeoff between reaching phase and sliding phase. Hence, the sliding surface is moved by changing the magnitude of the slope by adaptive law and varying the intercept by tuning algorithm. Simulations performed using a scaled 3D mathematical model of the crane confirm that the proposed control scheme can keep the horizontal position of the payload invariable and suppress the swing of the payload effectively during the hoisting or lowing process.

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References

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Figures

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Fig. 1

Coordinate frames of a 3D overhead crane

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Fig. 2

Direct adaptive fuzzy moving sliding mode PI control structure for 3D overhead crane

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Fig. 3

The regulation performance: the x-position (traveling distance), y-position (traversing distance), and z-position (rope length)

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Fig. 4

The swing angles in the x-direction (θx) and the y-direction (θy)

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Fig. 5

The control inputs fx, fy, and fl of the closed-loop system

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Fig. 6

The initial slope and final slope of position moving sliding surface

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Fig. 11

The trajectories V˙(t) of the nominal system, with +10% system uncertainties and with −10% system uncertainties

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