A Fuzzy Adaptive Force Controller Design of Robotic Manipulators for Pick-and-Placing Thin Brittle Materials

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For the pick-and-place operations of GDL, this paper presents and obtains the control system model using system identification method, and analyzes three distinct stages for the motion characteristics in pick-and-place operations. To satisfy the stick requirements for contact force control, a force controller based on fuzzy adaptive PID algorithm and a position controller based on feed-forward control are presented and designed. Simulations are carried out to verify the feasibility and effectiveness of the proposed control method. The above control strategies and methods are applied to pick up and place GDL. They can also be extended to the pick-and-place operations of the chips and other filed, which has broad application prospects.

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1666-1673

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February 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] RP. O'Hayre, SW. Cha, W. Colella and FB. Prinz . Fuel Cell Fundamentals, Wiley Press, Online Library, (2005).

Google Scholar

[2] V. Mehta, JS. Cooper, Review and analysis of PEM fuelcell design and manufacturing, Journal of Power Sources, Vol. 114, No. 1(2003), pp.32-53.

Google Scholar

[3] S. Jung, TC. Hsia, RG. Bonitz, Force tracking impedance control of robot manipulators under unknown environment, IEEE transaction on control systems Technology, Vol. 12, No. 3(2004), pp.474-483.

DOI: 10.1109/tcst.2004.824320

Google Scholar

[4] RZ. Stanisic, AV. Fernandez, Adjusting the parameters of the mechanical impedance for velocity, impact and force control, Robotica, Vol. 27(2012), pp.583-597.

DOI: 10.1017/s0263574711000725

Google Scholar

[5] C.C. Cheah, S. Kawamura and S. Arimoto, Stability of hybrid position and force control for robotic manipulator with kinematics and dynamics uncertainties, Automatica, Vol. 39, No. 5(2003), p.847–855.

DOI: 10.1016/s0005-1098(03)00002-5

Google Scholar

[6] K. Ahn, S. Yokota, Robust force control of a 6-link electro-hydraulic manipulator,. JSME International Journal, Vol. 46, No. 3(2003), pp.1091-1099.

DOI: 10.1299/jsmec.46.1091

Google Scholar

[7] G. Zhang, Y. Fu, R. Yang, Fuzzy grey prediction force control scheme based on outer force control loop, Chinese Journal of Mechanical Engineering, Vol. 40, No. 12(2004), pp.177-181.

DOI: 10.3901/jme.2004.12.177

Google Scholar

[8] CP. Bechlioulis, Z. Doulgeri and GA. Rovithakis, Neuro-Adaptive Force/Position Control With Prescribed Performance and Guarantee contact Maintenance, IEEE TRANSACTIONS ON NEURAL NETWORKS, Vol. 21, No. 12(2010), pp.1857-1868.

DOI: 10.1109/tnn.2010.2076302

Google Scholar

[9] John H. Lilly. Foundations of fuzzy control, Wiley Press, Online Library, (2007).

Google Scholar

[10] W. Ji, et al., Adaptive fuzzy PID composite control with hysteresis-band switching for line of sight stabilization servo system, Aerospace Science and Technology, Vol. 178, No. 5(2011), pp.25-32.

DOI: 10.1016/j.ast.2010.05.006

Google Scholar

[11] X. Dong, Z. Jian-qu and W. Feng, Fuzzy PID Control To Feed Servo System of CNC Machine Tool, Procedia Engineering, Vol. 29, No. 0(2012), pp.2853-2858.

DOI: 10.1016/j.proeng.2012.01.403

Google Scholar

[12] Y. Juang, Y. Chang and C. Huang, Design of fuzzy PID controllers using modified triangular membership functions, Information Sciences, Vol. 178, No. 5(2008), pp.1325-1333.

DOI: 10.1016/j.ins.2007.10.020

Google Scholar