Motion Control of Five Bar Linkage Manipulator Using Conventional Controllers Under Uncertain Conditions

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Gopal Krishan 1,* V. R. Singh 2

1. TIT&S, Bhiwani, Haryana-127021, India

2. PDM College of Engineering & Technology, Bahadurgarh, Haryana-124507, India

* Corresponding author.


Received: 1 Aug. 2015 / Revised: 17 Nov. 2015 / Accepted: 22 Jan. 2016 / Published: 8 May 2016

Index Terms

Motion Control, Robotic Manipulator, Trajectory Tracking, Sliding Mode Control, Computed Torque Control


Robot trajectory tracking has been the core functioning unit in the modern industrial environment wherein the accuracy in the motion control of robotic manipulators is the main area of research. Based on the fact that the working of these automatic robotic machines is highly influenced by the disturbances, this paper constitutes various conventional controllers for the motion control of five bar linkage manipulator. To verify the performance of proposed conventional controllers, these are made to work with two different trajectories. Common disturbances like payload & friction has been incorporated in the five bar linkage manipulator system for validation purpose. Simulation results prove that the performance of SMC based controller is better when compared with other conventional controllers.

Cite This Paper

Gopal Krishan, V. R. Singh, "Motion Control of Five Bar Linkage Manipulator Using Conventional Controllers Under Uncertain Conditions", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.5, pp.34-40, 2016. DOI:10.5815/ijisa.2016.05.05


[1]Astrom K.J. and Hagglund T., PID Controllers: Theory design and tuning. Instrument Society of America: Research Triangle Park, N.C. 1995.
[2]Dwyer A. O., Handbook of PI and PID Controller Tuning Rules. London, Britain: Imperial College Press, 2003.
[3]Choi, Chung and Suh, Performance and H∞ optimality of PID trajectory tracking control for lagrangian system. IEEE Transactions on Robotics and Automation. 16(7), December 2001.
[4]Goel A., Uniyal A., Bahuguna A., R. Patwal S., and Ahmed H., Performance Comparison of PID and Fuzzy Logic Controller using Different Defuzzification Techniques for Positioning Control of DC Motors. Journal of Information Systems and Communication. 3(1) : 235-238, 2012. [5] Kelly R., PD control with desired gravity compensation of robotic manipulators: a review. International Journal of Robotic Systems. 16(5) : 660-672, 1997.
[5]Chen Q., Chen H., Wang Y. and Woo P., Global stability analysis for some trajectory-tracking control schemes of robotic manipulators. Journal of Field Robotics. 18(2) : 69-75, 2001.
[7]Utkin V. I., Variable structure systems with sliding modes. IEEE Trans. Autom. Control. AC-22(2) : 212-222, 1977.
[8]Utkin V. I., Sliding Mode in Control and Optimization. New York: Springer-Verlag, 1992.
[9]Hung J. Y., Gao W., and Hung J. C., Variable structure control: a Survey. IEEE Trans. Ind. Electr. vol. 40 : 2-22, 1993.
[10]Young K. D., Utkin V. I., and Özgüner Ü., A control engineer's guide to sliding mode control. IEEE Trans. Control Sys. Tech. vol. 7 : 328-342, 1999.
[11]Abidi K. and Šabanovic A., Sliding-Mode Control for High- Precision Motion of a Piezostage, IEEE Transactions on Industrial Electronics. 54(1) : 629-637, 2007.
[12]Bristow D. A. and Alleyne A. G., A High Precision Motion Control System With Application to Microscale Robotic Deposition. IEEE Transactions on Control Systems Technology. 14(6) : 1008-1020, 2006.
[13]Ghorbel F., Chételat O. and Longchamp R., A Reduced Model for Constrained Rigid Bodies with Application to Parallel Robots. In Proc. of the IFAC Symposium on Robot Control SYROCO'94, Capri, 1994.
[14]Bartolini G., Pisano A. and Usai E., Digital Second-Order Sliding Mode Control for Uncertain Nonlinear Systems. Automatica. 37(9) : 1371-1377, 2001.
[15]Merlet J. P., Parallel robots. 2nd ed. Dordrecht, the Netherlands: Springer, 2006.
[16]Eshaghi S., Kharrati H., Badamchizadeh M.A. and Hasanzadeh I., A predictive controller based on dynamic matrix control for a nonminimum phase robot manipulator. International Journal of Control, Automation and Systems. 10(3) : 574-581, 2012.
[17]Armstrong-Helouvry B., Dupont P. and Canudas C., A Survey of Models, analysis tool and compensation methods for the control of machines with friction. Automatica. 30(7) : 1083-1138, 1994.
[18]Acob J. M., Pano V. and Ouyang P. R., Hybrid PD Sliding Mode Control of a Two Degree of- Freedom Parallel Robotic Manipulator. In Proc. of the 10th IEEE International Conference on Control and Automation (ICCA), China, 2013.
[19]Kankashwar M.R. and Kharrati H., Design of Multivariable Controller Based on Feedback Linearization for Five-Bar Linkage Manipulator. In Proc. of the 23rd Iranian Conference on Electrical Engineering (ICEE), Iran, 2015.
[20]Hassanjadeh I., Kharrati H. and Bonab J.R., Model Following Adaptive Control for a Robot with Flexible Joints. In Proc. of Canadian Conference on Electrical & Computer Engineering (CCECE), Canada, 2008.
[21]Hassanjadeh I., Mobayen S. and Kharrati H., Design of MIMO Controller for a Manipulator using Tabu Search Algorithm. In Proc. of International Conference on Intelligent and Advanced Systems (ICIAS), 2007.
[22]Kwok D.P. and Sheng F., Genetic Algorithm and Simulated Annealing for Optimal Robot Arm PID Control. In Proc. of IEEE World Congress on Computational Intelligence, 1994.
[23]Rodger S., Fossen T.I. and Kokotovic P.V., Robust Output Maneuvering for a Class of Non-Linear Systems. Automatica 40(3) : 373-383, 2004.
[24]Eshaghi S., Kharrati H., Badamchizadeh M.A. and Hasanzdeh I., A Predictive Controller Based on Dynamic Matrix Control for a Non-Minimum Phase Robot Manipulator, International Journal of Control, Automation & Systems, 10(3) : 574-581, 2012.
[25]Ouyang P.R.,, Revisiting Hybrid Five Bar Mechanism : Position Domain Control Application. In Proc. of IEEE International Conference on Information & Automation (ICIA), 2014.
[26]Nazari I., Hosainpour A., Piltan F., Emamzadeh S. and Mirzaie M., Design Sliding Mode Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Intelligent Systems and Applications, vol. 04 : 63-75, 2014.