magazinelogo

Journal of Applied Mathematics and Computation

ISSN Online: 2576-0653 Downloads: 226745 Total View: 2259573
Frequency: quarterly ISSN Print: 2576-0645 CODEN: JAMCEZ
Email: jamc@hillpublisher.com
Article Open Access http://dx.doi.org/10.26855/jamc.2018.05.003

Fuzzy Logic Based Position Control of Triglide Robot

Muhammet AYDIN1,*, Oğuz YAKUT2

1Firat University, Department of Mechatronics Engineering, Elazig, Turkey

2Firat University, Department of Mechatronics Engineering, Elazig, Turkey

*Corresponding author: Muhammet AYDIN

Published: May 24,2018

Abstract

In this paper, three degrees of freedom triglide parallel robot which is usually used in pick and place operations has been controlled. Triglide robot has been controlled by using fuzzy logic control method via a program written in Matlab being used dynamic equations with inverse and forward kinematic solutions of the robot. The derivative of error and error has been preferred as the input in the fuzzy logic structure. As the output, the control signal is generated from the fuzzy logic structure. The limit values of the membership functions of the fuzzy logic controller were found by optimization using the genetic algorithm via a program written in the Matlab package program. The controls have been repeated for three different reference points to demonstrate the success of the fuzzy logic controller on the triglide parallel robot. The system responses have been obtained graphically with the controls applied to the triglide parallel robot and the results have been examined. As a result, it is obviously seen that the system has reached the desired reference values approximately in 0.16 seconds with the fuzzy logic controller.

References

[1] Sciavicco, L. and Siciliano, B. (2000) Modeling and Control of Robot Manipulator (2thed.). Springer.

[2] Merlet, J.P. (2006) Parallel Robots (2th ed.). Springer, pp. 75-76.

[3] Proceedings of IEEE International Conference on Robotics and Automation (1992) “On the infinitesimal motion of parallel manipulators in singular configurations” Nice, France, Merlet, J.P., No. 1, pp. 320–325.

[4] Bi, Z. M. and Lang, S. Y. T. (2009), “Joint workspace of parallel kinematic machines”, Robotics and Computer Integrated Manufacturing, No. 25, pp. 57-63.

[5] Merlet, J. P. (1995), “Determination of the orientation workspace of parallel manipulators”, Journal of Intelligent and Robotic Systems, No. 13, pp. 143–160.

[6] SCOReD 2007 : The 5th Student Conference on Research and Development (2007)“Forward kinematics of 3 degrees of freedom delta robot” Malasia, Mustafa, M., Misuari, R. and Daniyal, H.

[7] Merlet, J. P. (2006) Parallel Robots (2th ed.). Springer, pp. 31-34.

[8] HSI 2008 (2008) “Evolutionary approach to optimal design of 3 dof translation exoskeleton and medical parallel robots” Krakow, Poland, Stan, S.D., Manic, M., Matieş, V. and Balan, R., pp. 720-725.

[9] TOK 2012 (2012) “Üç serbestlik dereceli Triglide paralel robotun ters ve düz kinematic çözümlerinin analitik olarak elde edilmesi” Nigde, Turkey, Aydın, M. and Alli, H.

[10] In: Proc. of the International Conference on Advances in Mechanical and Automation Engineering (2016) “The Obtaining of Dynamic Equations for Three Degree of Freedom Parallel Robot “Roma, İtaly, Aydın M, Alli H.

[11] Zadeh L. A. (1965), “Fuzzy Sets”, Information and Control, No. 8, pp. 338-353.

[12] Mamdani E. H., Assilion S (1974) “An Experiment in Linguistic Synthesis With a Fuzzy Logic Controller”, International Journal of Man-Machine Studies, No. 7, pp.1-13.

[13] Holmblad L. P., Ostergaard J. J. (1982) “Control of Cement Kiln by Fuzzy Logic”, Fuzzy Information and Decision Processes, pp. 389-399.

[14] Castillo O., Neyoy H., Soria J., Melin P., Valdez F. (2015) “A new approach for dynamic fuzzy logic parameter tuning in Ant Colony Optimization and its application in fuzzy control of a mobile robot”, Applied Soft Computing, No. 28, pp. 150–159.

[15] Abdessemed F., Faisal M., Emmadeddine M., Hedjar R., Al-Mutib K., Alsulaiman M., Mathkour H. (2014) “A Hierarchical Fuzzy Control Design for Indoor Mobile Robot”, International Journal of Advanced Robotic Systems, 2014, No. 11:33.

[16] Kayacan E., Kayacan E., Ramon H., Saeys W. (2013) “Adaptive Neuro-Fuzzy Control of a Spherical Rolling Robot Using Sliding-Mode-Control-Theory-Based Online Learning Algorithm”, IEEE Transactions On Cybernetıcs, 43:1.

[17] Siradjuddin I., Behera L., McGinnity T. M., Coleman S. (2014) “Image-Based Visual Servoing of a 7-DOF Robot Manipulator Using an Adaptive Distributed Fuzzy PD Controller”, IEEE/ASME Transactions On Mechatronics, 19:2.

[18] Zhou Q., Li H., Shi P. (2015) “Decentralized Adaptive Fuzzy Tracking Control for Robot Finger Dynamics”, IEEE Transactions On Fuzzy Systems, 23:3.

[19] Juang C-F., Chen Y-H., Jhan Y-H. (2015) “Wall-Following Control of a Hexapod Robot Using a Data-Driven Fuzzy Controller Learned Through Differential Evolution”, IEEE Transactions On Industrial Electronics, 62:1.

[20] Li Z., Xiao S., Ge S. S., Su H. (2016) “Constrained Multilegged Robot System Modeling and Fuzzy Control With Uncertain Kinematics and Dynamics Incorporating Foot Force Optimization”, IEEE Transactions On Systems, Man, And Cybernetics: Systems, 46:1.

[21] Li H., Wu C., Yin S., Lam H-K.(2016) “Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Unmeasurable Premise Variables”, IEEE Transactions On Fuzzy Systems, 24:5.

[22] Takahashi Y., Ishii T., Todoroki C., Ma eda Y. I., Nakamura T. (2015) “Fuzzy Control for a Kite-Based Tethered Flying Robot”, Journal of Advanced Computational Intelligence and Intelligent Informatics, 19:3.

[23] Sancheza M. A., Castillo O., Castro J. R. (2015) “Generalized Type-2 Fuzzy Systems for controlling a mobile robot and a performance comparison with Interval Type-2 and Type-1 Fuzzy Systems”, Expert Systems with Applications, No. 42, pp. 5904–5914.

[24] Melin P., Astudillo L., Castillo O., Valdez F., Garcia M. (2013) “Optimal design of type2 and type-1 fuzzy tracking controllers for autonomous mobile robots under perturbed torques using a new chemical optimization paradigm”, Expert Systems with Applications, No. 40, pp. 3185–3195.

How to cite this paper

Fuzzy Logic Based Position Control of Triglide Robot

How to cite this paper: Muhammet AYDIN, Oğuz YAKUT. (2018) Fuzzy Logic Based Position Control of Triglide RobotJournal of Applied Mathematics and Computation2(5), 188-200.

DOI: http://dx.doi.org/10.26855/jamc.2018.05.003