Fuzzy Synergetic Control for Dynamic Car-Like Mobile Robot

Zoulikha Bouhamatou; Foudil Abedssemed

doi:10.2478/ama-2022-0007

References

1. Ahifar A, Ranjbar AN, Rahmani Z. Finite Time Terminal Synergetic Controller for Nonlinear Helicopter Model. 2019; 32(2):236–241.10.5829/ije.2019.32.02b.08
Search in Google Scholar Back to article
2. Benaziza W, Slimane N, Mallem A. Disturbances elimination with fuzzy sliding mode control for mobile robot trajectory tracking. Advances in Electrical and Electronic Engineering. 2018; 16(3):297–310. https://doi.org/10.15598/aeee.v16i3.276710.15598/aeee.v16i3.2767
Search in Google Scholar Back to article
3. Bhattacharyya S, Shimoda S, Hayashibe M. A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control. IEEE Transactions on Systems Man and Cybernetics: Systems 2016; 46(7):957–968. https://doi.org/10.1109/TSMC.2016.256053210.1109/TSMC.2016.2560532
Search in Google Scholar Back to article
4. Dung NM, Duy VH, Phuong NT, Kim SB, Oh MS. Two-wheeled welding mobile robot for tracking a smooth curved welding path using adaptive sliding-mode control technique. International Journal of Control Automation and Systems. 2007; 5(3):283–294.
Search in Google Scholar Back to article
5. Elhariri E, El-Bendary N, Hassanien AE, Abraham A. Grey wolf optimization for one-against-one multi-class support vector machines. 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR). 2015; 7–12. https://doi.org/10.1109/SOCPAR.2015.749278110.1109/SOCPAR.2015.7492781
Search in Google Scholar Back to article
6. Gupta S, Deep K. Cauchy Grey Wolf Optimiser for continuous optimisation problems. Journal of Experimental & Theoretical Artificial Intelligence. 2018; 30(6):1051–1075 https://doi.org/10.1080/0952813X.2018.1513080.10.1080/0952813X.2018.1513080
Search in Google Scholar Back to article
7. Humaidi AJ, Ibraheem IK, Azar AT, Sadiq ME. A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles. Entropy. 2020; 22(7). https://doi.org/10.3390/e2207072310.3390/e22070723751726233286496
Search in Google Scholar Back to article
8. Ibrahim AEB. Wheeled Mobile Robot Trajectory Tracking using Sliding Mode Control. 2016. https://doi.org/10.3844/jcssp.2016.48.5510.3844/jcssp.2016.48.55
Search in Google Scholar Back to article
9. Kamalova A, Navruzov S, Qian D, Lee SG. Multi-Robot Exploration Based on Multi-Objective Grey Wolf Optimizer. Applied Sciences. 2019; 9(14). https://doi.org/10.3390/app914293110.3390/app9142931
Search in Google Scholar Back to article
10. Kolesnikov A, Veselov G, Kolesnikov A. Modern applied control theory: synergetic approach in control theory. TRTU Moscow Taganrog. 2000; 4477–4479.
Search in Google Scholar Back to article
11. Liu CH, Hsiao MY. A finite time synergetic control scheme for robot manipulators. Computers and Mathematics with Applications. 2012; 64(5):1163–1169. https://doi.org/10.1016/j.camwa.2012.03.05810.1016/j.camwa.2012.03.058
Search in Google Scholar Back to article
12. Mallem A, Slimane N, Benaziza W. Dynamic Control of Mobile Robot Using RBF Global Fast Sliding mode. IAES International Journal of Robotics and Automation (IJRA). 2018; 7(3):159. https://doi.org/10.11591/ijra.v7i3.pp159-16810.11591/ijra.v7i3.pp159-168
Search in Google Scholar Back to article
13. Mesquita EDEM, Sampaio RC, Vicente H, Ayala H, Llanos CH. Recent Meta-Heuristics Improved by Self-Adaptation Applied to Nonlinear Model-Based Predictive Control. 2020; 118841–118852.10.1109/ACCESS.2020.3005318
Search in Google Scholar Back to article
14. Mirjalili S, Mirjalili SM, Lewis A. Grey Wolf Optimizer. Advances in Engineering Software. 2014; 69:46–61. https://doi.org/ https://doi.org/10.1016/j.advengsoft.2013.12.00710.1016/j.advengsoft.2013.12.007
Search in Google Scholar Back to article
15. Mittal N, Singh U, Sohi BS. Modified Grey Wolf Optimizer for Global Engineering Optimization. Applied Computational Intelligence and Soft Computing. 2016; 1–16. https://doi.org/10.1155/2016/795034810.1155/2016/7950348
Search in Google Scholar Back to article
16. Peng S, Shi W. Adaptive fuzzy integral terminal sliding mode control of a nonholonomic wheeled mobile robot. Mathematical Problems in Engineering. 2017. https://doi.org/10.1155/2017/367184610.1155/2017/3671846
Search in Google Scholar Back to article
17. Podvalny SL, Vasiljev EM. Synergetic control of UAV on the basis of multi-alternative principles. International Russian Automation Conference RusAutoCon. 2018; 1–6. https://doi.org/10.1109/RUSAUTOCON.2018.850172710.1109/RUSAUTOCON.2018.8501727
Search in Google Scholar Back to article
18. Sklyarov AA, Veselov GE, Sklyarov SA, Pohilina TE. Synthesis of the synergetic control law of the transport robotic platform. Proceedings of 2017 IEEE 2nd International Conference on Control in Technical Systems CTS. 2017; 285–288. https://doi.org/10.1109/CTSYS.2017.810954710.1109/CTSYS.2017.8109547
Search in Google Scholar Back to article
19. Veselov G, Sklyrov A, Mushenko A, Sklyrov S. Synergetic Control of a Mobile Robot Group. Proceedings - 2nd International Conference on Artificial Intelligence Modelling and Simulation AIMS. 2014; 155–160. https://doi.org/10.1109/AIMS.2014.2210.1109/AIMS.2014.22
Search in Google Scholar Back to article
20. Yeh YC, Li THS., Chen CY. Adaptive fuzzy sliding-mode control of dynamic model based car-like mobile robot. International Journal of Fuzzy Systems. 2009; 11(4):272–286. https://doi.org/10.30000/IJFS.200912.0006.
Search in Google Scholar Back to article