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Optimal Design of Super Twisting Control with PSO Algorithm for Robotic Manipulator
Azza Elsayed Ibrahim, Sawsan Gharghory
Pages - 1 - 15     |    Revised - 30-11-2018     |    Published - 31-12-2018
Volume - 9   Issue - 1    |    Publication Date - December 2018  Table of Contents
Super Twisting Control, Sliding Mode Control, Particle Swarm Optimization Method, Robotic Manipulator, Robust Optimal Control.
Robotic manipulators are nonlinear and coupling systems exposing to external disturbance. They are used in wide industrial applications; the suitable selection of a nonlinear robust controller is required. Sliding Mode Controller (SMC) was designed to achieve these requirements, but unfortunately the chattering phenomenon was the main drawback of the conventional SMC. It leads to destructive of some components of a real system and subsequent loss in its accuracy. Hence, the design of Super-Twisting Controller (STC) is suggested for chattering elimination. In previous literatures, the accomplishment of the manual adjustment for the parameters of STC was a large burden and time consuming process. Therefore, a new combination of Particle Swarm Optimization (PSO) algorithm with STC is proposed for optimal tuning of STC parameters. The simulation results demonstrate the superiority of the super twisting technique for chattering mitigation comparing to the conventional SMC. Also, STC tuned via PSO proves its effectiveness and robustness to different types of external disturbances without the needs for the knowledge of their upper boundary values. Besides, the performance of the controlled system is faster and more accurate in the criteria of overshoot, settling time and rise time compared to the manual adjusting of super twisting controllers.
1 Google Scholar 
2 BibSonomy 
3 Doc Player 
4 Scribd 
5 SlideShare 
A. Levant, "Chattering analysis", IEEE Transactions on Automatic Control, vol. 55, no. 6, pp. 1380- 1389, 2010.MathSciNetCrossRefGoogle Scholar
A. Levant. Higher-order sliding modes, differentiation and output-feedback control. International Journal of Control, vol. 76, no. 9, pp. 924-941, 2003.MathSciNetCrossRefMATHGoogle Scholar.
Angeline, P.J.: Using selection to improve particle swarm optimization. Proceedings of Congress on Evolutionary Computation, Anchorage 4-9 May 1998, pp. 84-89 doi:10.1109/ICEC.1998. 699327.
Ashpana Shiralkar, and Shailaja Kurode, " Generalized Super-Twisting Algorithm for Control of Electro-Hydraulic Servo System ", Volume 49, Issue 1, 2016, Pages 742-747, 2405-8963 © 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Peer review under responsibility of International Federation of Automatic Control. 10.1016/j.ifacol.2016.03.14.
Azza El-sayed Ibrahim "Wheeled Mobile Robot Trajectory Tracking using Sliding Mode Control ", Journal of Computer Sciences 2016, 12 (1): 48.55, DOI: 10.3844/jcssp.2016.48.55.
B.R. Markiewicz. "Analysis of the Computed Torque Drive Method and Comparison with Conventional Position Servo for a Computer-Controlled Manipulator," NASA-JPL Technical Memo, 33-61, Mar. 1973.
Belmecheri, F., Prins, C., Yalaoui, F., Amodeo, L.: "Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows". J. Intell. Manuf. 24 (4), 775-789 (2013).
C. Kunusch et al., Sliding-Mode Control of PEM Fuel Cells, Advances in Industrial Control, DOI 10.1007/978-1-4471-2431-3_3, © Springer-Verlag London Limited 2012.
Chiew Tsung Heng, Zamberi Jamaludin, Ahmad Yusairi Bani Hashim, Lokman Abdullah, and Nur Aidawaty, Rafan "Design of Super Twisting Algorithm for Chattering Suppression in Machine Tools " , International Journal of Control, Automation and Systems 15(3) (2017) 1259-1266, ICROS, KIEE and Springer 2017.
Dastranj MR, Moghaddas M, Ghezi Y, Rouhani M. "Robust control of inverted pendulum using fuzzy sliding mode control and genetic algorithm". Int J Info Elect Eng 2012; 2: 773-776.
Demirtas M. "DSP-based sliding mode speed control of induction motor using neuro-genetic structure". Int J Exp Sys Appl 2009; 36: 5533-5540.
F. Plestan, A. Glumineau, S. Laghrouche, "A new algorithm for high-order sliding mode control", international journal of robust and nonlinear control Int., J. Robust Nonlinear Control 2008; 18:441- 453. Published online 6 June 2007 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/rnc.1234.
Hasanifard, Goran, Habib Nejad Korayem, Moharam, and Nikoobin, Amin, "Robust Nonlinear Control of Two Links Robot manipulator and Computing Maximum Load ", World Academy of Science, Engineering and Technology 50 2009.
Hroncová Darina , Bakši Jaroslav, "A Two Link Manipulator End Effector Control ",American Journal of Mechanical Engineering. 2017, 5(6), 239-242. DOI: 10.12691/ajme-5-6-1.
Itzhak Levi, Nadav Berman and Amit Ailon, "Robust Adaptive Nonlinear H8 Control for Robot Manipulators", proceedings of 15th Mediterranean Conference on Control & Automation, July 27-29, 2007, Athens - Greece.
J. Angeles. "Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms". Springer, 2006.
K. David Young, Vadim I. Utkin, "A Control Engineer's Guide to Sliding Mode Control", IEEE transactions on control systems technology, vol. 7, no. 3, may 1999.
Kennedy J. and Eberhart C., "Particle Swarm Optimization", Proceedings of the IEEE International Conference on Neural Networks, Australia, pp. 1942-1948, 1995.
Kim, B.-I., Son, S.-J.: A probability matrix based particle swarm optimization for the capacitated vehicle routing problem. J. Intell. Manuf. 23(4), 1119-1126 (2012).
M. DAL, R. Teodorescu, "Sliding mode controller gain adaptation and chattering reduction techniques for DSP-based PM DC motor drives.", Turk J Elec. Eng & Comp Sci., Vol.19, No.4, 2011.
Ming-Lei Tseng and Min-Shin Chen, "chattering reduction of sliding mode control by low-pass filtering the control signal", Asian Journal of Control, Vol. 12, No. 3, pp. 392 398, May 2010.
Mohamed Sayed, Sawsan M. Gharghory and Hanan Kamal, "Gain tuning PI controllers for boiler turbine unit using a new hybrid jump PSO", Journal of Electrical Systems and Information Technology (JESIT), April, 2015 Journal of Electrical Systems and Information Technology 2 (2015) 99-110.
Mohamed Sayed, Sawsan M. Gharghory and Hanan Kamal," Euclidean distance-based multi-objective particle swarm optimization for optimal power plant set points", Journal of Energy System(ENSY), December, 2015. Springer, Vol. 7, PP. 569-583.
Moreno and M. Osorio, "Strict Lyapunov functions for the super-twisting algorithm ," IEEE Trans. on Automatic Control, vol.57, no. 4, pp. 1035-1040, 2012.
Nasri A, Hazzab A, Bousserhane IK, Hadjeri S, Sicard P. Two wheel speed robust sliding mode control for electric vehicle drive. Serb J Elect Eng 2008; 5: 199-216.
R. Dhanasekar , S. Ganesh Kumar ; M. Rivera " Sliding mode control of electric drives/review ", Automatica (ICA-ACCA), IEEE International Conference on 19-21 Oct. 2016, DOI: 10.1109/ICA- ACCA.2016.7778466.
R. Featherstone and D. E. Orin. "Robot dynamics: Equations and algorithms". In IEEE Conf. on Robotics and Automation, pages 826-834, San Francisco, CA, April 2000.
Ray-I Chang, Shu-Yu Lin, Yuhsin Hung," Particle swarm optimization with query-based learning for multi-objective power contract problem", Expert System Applications, Vol. 39, Issue 3, PP.3116-3126, Sep. 2011.
Raymond Chuei, Zhenwei Cao, and Zhihong Man, "Design of Super Twisting Repetitive Control ", 978- 1-4673-8644-9/16/$31.00 c 2016 IEEE.
Rincy Koshy, Jayasree P R, "Comparative Study of H-infinity and Sliding Mode Control for a Manipulator with Oscillatory-Base", 2017 International Conference on circuits Power and Computing Technologies [ICCPCT].
Senol I, Demirtas M, Rustemov S, Gumus B. "Position control of induction motor a new-bounded fuzzy sliding mode controller". COMPEL 2005; 24: 145-157.
Sonia Mahjoub, Fai Cal Mnif , Nabil Derbel, "Second-order Sliding Mode Approaches for the Control of a Class of Under actuated Systems", International Journal of Automation and Computing 12(2), April 2015, 134-141, DOI: 10.1007/s11633-015-0880-3.
T. J. Tarn, A. K. Bejczy, A. Isidori, and Y. Chen. "Nonlinear feedback in robot arm control," in Proc. IEEE Conference on Decision and Control, Las Vegas, 1984, pp. 736-751 'ORCID: Connecting research and researchers', http://orcid.org/, accessed 3 December 2014
Vadim I. Utkin , " Sliding Mode Control Design Principles and Applications to Electric Drives " , IEEE transactions on industrial electronics, vol. 40, no. 1, february 1993.
W. Perruquetti, J. P. Barbot. "Sliding Mode Control in Engineering", FL, USA: CRC Press, 2002. CrossRef Google Scholar.
Wang, K., Jun Zheng, Y.: A new particle swarm optimization algorithm for fuzzy optimization of armored vehicle scheme design. Appl. Intell. 37(4), 520-526 (2012).
Yakun Zhao, Panfeng Huang , Fan Zhang, "Dynamic modelling and Super-Twisting Sliding Mode Control for Tethered Space Robot ", Acta Astronautica 143 (2018) 310-321, 0094-5765/© 2017 IAA. Published by Elsevier Ltd. All rights reserved.
Yildiz, A.R., Solanki, K.N.: Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach. Int. J. Adv. Manuf. Technol. 59(1-4), 367-376 (2012).
Zheng, Z.,Wu, C.: "Power optimization of gas pipelines via an improved particle swarm optimization algorithm. Petrol". Sci. 9(1), 89-92 (2012).
Dr. Azza Elsayed Ibrahim
Engineering/ Computers and Systems Department Electronics Research Institute - Egypt
Dr. Sawsan Gharghory
Engineering/ Computers and Systems Department Electronics Research Institute - Egypt