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Research Papers

Fuzzy Sliding Mode Controller Design for a Cooperative Robotic System With Uncertainty for Handling an Object

[+] Author and Article Information
Maryam Farahmandrad

Department of Electrical Engineering,
Bu-Ali Sina University,
Hamedan 6516738695, Iran
e-mail: m.farahmandrad@alumni.basu.ac.ir

Soheil Ganjefar

Professor
Department of Electrical Engineering,
Bu-Ali Sina University,
Hamedan 6516738695, Iran
e-mail: s_ganjefar@basu.ac.ir

Heidar Ali Talebi

Professor
Department of Electrical Engineering,
Amirkabir University of Technology,
Tehran 1591634311, Iran
e-mail: alit@aut.ac.ir

Mahdi Bayati

Department of Electrical Engineering,
Amirkabir University of Technology,
Tehran 1591634311, Iran
e-mail: bayati.mahdi@aut.ac.ir

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received October 26, 2018; final manuscript received January 24, 2019; published online February 27, 2019. Editor: Joseph Beaman.

J. Dyn. Sys., Meas., Control 141(6), 061010 (Feb 27, 2019) (8 pages) Paper No: DS-17-1616; doi: 10.1115/1.4042742 History: Received October 26, 2018; Revised January 24, 2019

This paper proposes a control framework for a cooperative robotic system to grasp and handle an object with known geometry in the presence of uncertainty in robot dynamics. Based on passive decomposition approach, dynamic equations of the cooperative robotic system are decomposed into two decoupled systems, shape and locked systems. The locked system and the shape system are controlled by two fuzzy sliding mode controllers (SMCs). Stability is studied through passivity property and Lyapunov theorem. Simulation results confirm that the proposed control scheme works well.

Copyright © 2019 by ASME
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References

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Figures

Grahic Jump Location
Fig. 1

Shape and locked systems in the cooperative robotic system

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Fig. 2

The membership functions of the inputs, s and s˙

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Fig. 3

The membership functions of the output Kfuzz

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Fig. 4

Joint angles of each robot, θ and θ′

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Fig. 5

Two-dimensional Circular trajectory tracking of the locked system in XY plane

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Fig. 6

Trajectory tracking of the shape system

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Fig. 7

Trajectory tracking error of the locked system

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Fig. 8

Grasping shape error

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Fig. 9

Gains of the fuzzy SMCs for the locked system, kL

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Fig. 10

Gains of the fuzzy SMCs for the shape system, kS

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Fig. 11

Control torque of the first robot joints: (a) when the fuzzy SMCs are employed and (b) when the classical SMCs are employed

Grahic Jump Location
Fig. 12

Control torque of the second robot joints: (a) when the fuzzy SMCs are employed and (b) when the classical SMCs are employed

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Fig. 15

Two-dimensional circular trajectory tracking of the locked system in XY plane in the presence of disturbance

Grahic Jump Location
Fig. 16

Trajectory tracking of the shape system in the presence of disturbance

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