ITM Web Conf.
Volume 52, 2023International Conference on Connected Object and Artificial Intelligence (COCIA’2023)
|Number of page(s)||7|
|Published online||08 May 2023|
- Karaboga, D., Kaya, E. Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey. Artif Intell Rev 52, 2263–2293 (2019). [CrossRef] [Google Scholar]
- H. Asada & J.J. Slotine, “Robot analysis and Control”, New york:Wiley, 1986. [Google Scholar]
- Anh-Tu Nguyen; Tadanari Taniguchi et all, ’Fuzzy Control Systems: Past, Present and Future’, IEEE Computational Intelligence Magazine ( Volume: 14, Issue: 1, February 2019) [Google Scholar]
- P. Sumathi, “Precise tracking control of robot manipulator using fuzzy logic”, DARH2005 conference, session4.1. [Google Scholar]
- Mohammed Salah Abood; Isam Kareem Thajeel et all, Fuzzy Logic Controller to control the position of a mobile robot that follows a track on the floor, 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). [Google Scholar]
- M. Kevin, Passino and Stephan Yurkovich, “Fuzzy logic”, Addison Wesley longman 1998. [Google Scholar]
- Jang J. S. R. “Adaptive network based fuzzy inference systems”, IEEE Transactions on systems man and cybernetics 1993, p. 665-685. [CrossRef] [Google Scholar]
- B. Allaoua, A. Laoufi, B. Gasbaoui, and A. Aabderrahmani, “Neuro-Fuzzy DC Motor Speed Control Using Particle Swarm Optimization”, Leonardo Electronic Journal of Practices and Technologies Issue 15, July-December 2009 [Google Scholar]
- F. Baghli, L. El bakkali, “Artificial Intelligence Application’s for a Robot Manipulator with Two Degrees of Freedom Position Control” International Journal of Mechatronics, Electrical and Computer Technology Vol. 4(11), Apr. 2014, pp. 349-368. [Google Scholar]
- Lin C. T., Lee C. S. G. Neural fuzzy systems: A neuro-fuzzy synergism to intelligent systems. Upper Saddle River, Prentice-Hall, 1996. Constantin V. A. Fuzzy logic and neuro-fuzzy applications explained. Englewood Cliffs, Prentice-Hall, 1995. [Google Scholar]
- F. Z. Baghli, L. El Bakkali, Y. Lakhal, A. Nasri, and B. Gasbaoui, “Arm Manipulator Position Control Based On Multi-Input Multi-output PID Strategy”. Journal of Automation, Mobile Robotics and Intelligent Systems 8 (2):36-39 (2014). [Google Scholar]
- Kim J., Kasabov N. Hy FIS, Adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. Neural Networks, 1999. [Google Scholar]
- F. Z. Baghli, L. El Bakkali, Y. Lakhal, A. Nasri, and B. Gasbaoui, “The efficiency of the inference system knowledge strategy for the position control of a robot manipulator with two degree of freedom”, International Journal of Research in Engineering and Technology, Volume: 02 Issue: 07 Jul [Google Scholar]
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