A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

Mohamed Boukens; Abdelkrim Boukabou; Mohammed Chadli

doi:10.1109/JAS.2018.7511216

Volume 6 Issue 1

Jan. 2019

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2019 > 6(1): 84-96

Mohamed Boukens, Abdelkrim Boukabou and Mohammed Chadli, "A Real Time Self-Tuning Motion Controller for Mobile Robot Systems," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 84-96, Jan. 2019. doi: 10.1109/JAS.2018.7511216

Citation:

Mohamed Boukens, Abdelkrim Boukabou and Mohammed Chadli, "A Real Time Self-Tuning Motion Controller for Mobile Robot Systems," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 84-96, Jan. 2019. doi: 10.1109/JAS.2018.7511216

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A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

doi: 10.1109/JAS.2018.7511216

1.
Department of Electronics, University of Laghouat, B. P. 37G route de Ghardaia, Laghouat 03000, Algeria
2.
Department of Electronics, University of MSB Jijel, BP 98 Ouled Aissa, Jijel 18000, Algeria
3.
University of Picardie Jules Verne, 33 rue Saint-Leu 80039, Amiens, France

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Author Bio:
Mohamed Boukens received the M.E. degree and Ph.D. degree in electronics from University of Jijel, Algeria, in 2013 and 2017, respectively. Currently, he is an Assistant Professor at University of Laghouat. His current research interests include robotics and automation and real-time intelligent control in practical applications. (e-mail: m.boukens@lagh-univ.dz)

Abdelkrim Boukabou (M'14) received the Ph.D. degree from University of Constantine, Algeria in 2006. Currently, he is a Full Professor at the University of Jijel. His research interests include nonlinear control theory, robotics and automation, power-line communications, and smart grids. (e-mail: aboukabou@univjijel.dz)

Mohammed Chadli (SM'99) received the master degree (DEA) from the Engineering School INSALyon in 1999, the Ph.D. degree from the CRANNancy France in 2002 and his Habilitation in 2011 at the University of Picardie Jules Verne (UPJV) in Amiens, France. From 1999 to 2004, he was an Assistant Professor CRAN-INPL (Institut National Polytechnique de Lorraine). Since 2004, he has been Associate Professor at the UPJV-MIS France. He was a visiting professorship at the Technical University of Ostrava-Czech Rep., University of Agder, Nrway, University of Nanjing and University of Shanghai, China. His research interests include fuzzy/LPV and switched systems, singular systems, robust control, fault detection and isolation (FDI), fault tolerant control (FTC) via LMI, SOS and Lyapunov methods, and their applications (automotive control, renewable energy). He is author/co-author of 4 books, book chapters and numerous articles published in international journals and conferences.
Dr. Chadli is a senior member of IEEE, he is serving as an Editorial Board member for various peer-reviewed journals including IEEE Transaction on Fuzzy Systems, IET-Control Ttheory and Applications, Asian Journal of Control, Journal of Franklin Institute, etc., and was a Guest Editor for special issues in international journals. (e-mail: mohammed.chadli@u-picardie.fr)
Corresponding author: Mohammed Chadli, e-mail: mohammed.chadli@u-picardie.fr
Received Date: 2018-05-03
Revised Date: 2018-07-03
Accepted Date: 2018-07-10

Abstract

Abstract

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.
- Learning and adaptive systems,
- motion control,
- metaheuristic,
- robust control,
- real-time tuning,
- self-tuning,
- wheeled mobile robot

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References(23)

References

[1]	C. Özsoy and T. Şişman, "MIMO and SISO self-tuning hybrid position/force control of robotic manipulators, " J. Field Robot. , vol. 13, no. 1, pp. 41-51, Jan. 1996. http://www.onacademic.com/detail/journal_1000039971664910_bfb9.html
[2]	M. A. Ridao, E. F. Camacho, J. Riquelme, and M. Toro, "An evolutionary and local search algorithm for motion planning of two manipulators, " J. Field Robot. , vol. 18, no. 8, pp. 463-476, Aug. 2001. http://www.researchgate.net/publication/2877636_An_Evolutionary_And_Local_Search_Algorithm_For_Motion_Planning_of_two_manipulators?ev=sim_pub
[3]	A. Zdešar, D. Dovžan, and I. Škrjanc, "Self-tuning of 2 DOF control based on evolving fuzzy model, " Appl. soft Comput. , vol. 19, pp. 403-418, Jun. 2014.
[4]	C. Blum and A. Roli, "Metaheuristics in combinatorial optimization: Overview and conceptual comparison, " ACM Comput. Surv. , vol. 35, no. 3, pp. 268-308, Sep. 2003. http://www.tandfonline.com/servlet/linkout?suffix=cit0026&dbid=16&doi=10.1080%2F03772063.2017.1343157&key=10.1145%2F937503.937505
[5]	A. Homaifar, M. Bikdash, and V. Gopalan, "Design using genetic algorithms of hierarchical hybrid fuzzy-PID controllers of two-link robotic arms, " J. Field Robot. vol. 14, no. 6, pp. 449-463, 1997. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=6c9ca989ce7e732b30050b24aba2cad2
[6]	H. V. H. Ayala and L. dos Santos Coelho, "Tuning of PID controller based on a multiobjective genetic algorithm applied to a robotic manipulator, " Expert Syst. Appl. , vol. 39, no. 10, pp. 8968-8974, Aug. 2012. https://www.sciencedirect.com/science/article/pii/S0957417412002710
[7]	K. D. Sharma, A. Chatterjee, and A. Rakshit, "A PSO-Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision-based robot navigation, " IEEE Trans. Instrum. Measur. , vol. 61, no. 7, pp. 1908-1914, Jul. 2012. http://www.researchgate.net/publication/254060267_A_PSOLyapunov_Hybrid_Stable_Adaptive_Fuzzy_Tracking_Control_Approach_for_Vision-Based_Robot_Navigation
[8]	A. Rajasekhar, A. Abraham, and M. Pant, "A hybrid differential artificial bee colony algorithm based tuning of fractional order controller for permanent magnet synchronous motor drive, " Int. J. Mach. Learn. Cyber. , vol. 5, no. 3, pp. 327-337, Jun. 2014. doi: 10.1007/s13042-012-0136-2
[9]	W. J. Gu, Y. G. Yu, and W. Hu, "Artificial bee colony algorithmbased parameter estimation of fractional-order chaotic system with time delay, " IEEE/CAA J. of Autom. Sinica, vol. 4, no. 1, pp. 107-113, Jan. 2017. http://www.cnki.com.cn/Article/CJFDTotal-ZDHB201701012.htm
[10]	O. Castillo, H. Neyoy, J. Soria, P. Melin, and F. Valdez, "A new approach for dynamic fuzzy logic parameter tuning in ant colony optimization and its application in fuzzy control of a mobile robot, " Appl. Soft Comput. , vol. 28, pp. 150-159, Mar. 2015. https://www.sciencedirect.com/science/article/pii/S1568494614006140
[11]	S. Bououden, M. Chadli, and H. R. Karimi, "An ant colony optimization-based fuzzy predictive control approach for nonlinear processes, " Inf. Sci. , vol. 299, pp. 143-158, Apr. 2015. https://www.sciencedirect.com/science/article/pii/S002002551401161X
[12]	C. A. C. Parker and H. Zhang, "Biologically inspired collective comparisons by robotic swarms, " Int. J. Robot. Res. , vol. 30, no. 5, pp. 524-535, Mar. 2011. https://www.researchgate.net/publication/220122584_Biologically_inspired_collective_comparisons_by_robotic_swarms
[13]	D. Fister, I. Fister Jr, I. Fister, and R. Šafarič, "Parameter tuning of PID controller with reactive nature-inspired algorithms, " Robot. Autonom. Syst. , vol. 84, pp. 64-75, Oct. 2016. https://www.sciencedirect.com/science/article/pii/S0921889016301439
[14]	M. Boukens and A. Boukabou, "Design of an intelligent optimal neural network-based tracking controller for nonholonomic mobile robot systems, " Neurocomputing, vol. 226, pp. 46-57, Feb. 2017. https://www.sciencedirect.com/science/article/pii/S0925231216314308
[15]	G. J. Liu and A. A. Goldenberg, "Comparative study of robust saturation-based control of robot manipulators: analysis and experiments, " Int. J. Robot. Res. , vol. 15, no. 5, pp. 473-491, Oct. 1996. https://www.researchgate.net/publication/220121902_Comparative_Study_of_Robust_Saturation-Based_Control_of_Robot_Manipulators_Analysis_and_Experiments
[16]	J. Z. Peng, J. Yu, and J. Wang, "Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties, " ISA Trans. , vol. 53, no. 4, pp. 1035-1043, Jul. 2014. https://www.sciencedirect.com/science/article/abs/pii/S0019057814001013
[17]	M. M. Fateh and A. Arab, "Robust control of a wheeled mobile robot by voltage control strategy, " Nonlin. Dyn. , vol. 79, no. 1, pp. 335-348, Jan. 2015. doi: 10.1007/s11071-014-1667-8
[18]	M. Boukens, A. Boukabou, and M. Chadli, "Robust adaptive neural network-based trajectory tracking control approach for nonholonomic electrically driven mobile robots, " Robot. Autonom. Syst. , vol. 92, pp. 30-40, Jun. 2017. https://www.sciencedirect.com/science/article/pii/S0921889016301865
[19]	H. Zargarzadeh, "Lyapunov based optimal control of a class of nonlinear systems, " Ph. D. dissertation, Univ. Sci. Technol., Missouri, 2012. https://www.researchgate.net/publication/263200058_Lyapunov_based_optimal_control_of_a_class_of_nonlinear_systems
[20]	H. K. Khalil, Nonlinear Systems, 3rd ed. New Jersey, USA: Prentice Hall, 2002.
[21]	M. Dorigo, V. Maniezzo, and A. Colorni, "Ant system: optimization by a colony of cooperating agents, " IEEE Trans. Syst. Man Cybern. B: Cybern. , vol. 26, no. 1, pp. 1-13, Feb. 1996. http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM18263004
[22]	Z. D. Wang, L. C. Wang, S. Liu, and G. L. Wei, "Encoding-decoding based control and filtering of networked systems: insights, developments and opportunities, " IEEE/CAA J. of Autom. Sinica, vol. 5, no. 1, pp. 3-18, Jan. 2018.
[23]	L. C. Wang, Z. D. Wang, G. L. Wang, and F. E. Alsaadi, "Finite-time state estimation for recurrent delayed neural networks with component-based event-triggering protocol, " IEEE Trans. Neural Netw. Learn. Syst. , vol. 29, no. 4, pp. 1046-1057, Apr. 2018. https://www.ncbi.nlm.nih.gov/pubmed/28186909

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A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

doi: 10.1109/JAS.2018.7511216

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