Comparison of fractional order sliding mode controllers on robot manipulator

Mehmet Yavuz , Muhammet Öztürk , Burcu Yaşkıran

An International Journal of Optimization and Control: Theories & Applications ›› 2025, Vol. 15 ›› Issue (2) : 281 -293.

PDF (2404KB)
An International Journal of Optimization and Control: Theories & Applications ›› 2025, Vol. 15 ›› Issue (2) :281 -293. DOI: 10.36922/ijocta.1678
RESEARCH ARTICLE
research-article
Comparison of fractional order sliding mode controllers on robot manipulator
Author information +
History +
PDF (2404KB)

Abstract

Challenging and time-consuming tasks performed by humans can today be performed faster and more efficiently by robot manipulators with the development of technology. Robotic manipulators are flexible, can fit in small spaces, and are very effective for tasks that require high precision. They are widely used in the production lines of factories (handling, assembly, welding, etc.) and in fields that require manpower, such as medicine and engineering. Since it is used in tasks that require precision, its control is also important. Sliding modal control (SMC), one of the robust control methods, is a control method used in nonlinear systems because it can be applied to unstable systems, is easy to design and, has high accuracy against parameter uncertainties. However, it produces an unstable control signal within a certain range and this discontinuous control signal causes cracking in the system, which causes damage to the system elements. Especially in recent years, one of the most recent and successful methods used to reduce the chattering effect, which is the biggest problem in the SMC approach, is the fractional order design of the sliding surface. In the fractional order SMC (FOSMC) method, the derivative expression in the sliding surface is defined using the system variable’s error to be controlled and the derivative of the error is computed fractionally. In this paper, Caputo FOSMC (CFOSMC), defined with 3 different sliding surfaces using the Caputo fractional operator, is compared with classical SMC for controlling a 2-degree of-freedom (2-DOF) robot manipulator. According to the results obtained from simulation comparisons, it is observed that approach 3 gives better results than the other two approaches and classical SMC in terms of overshoot, settling and error value for some derivative orders.

Keywords

Robot manipulator / Sliding surface / Sliding mode control / Caputo fractional order operator

Cite this article

Download citation ▾
Mehmet Yavuz, Muhammet Öztürk, Burcu Yaşkıran. Comparison of fractional order sliding mode controllers on robot manipulator. An International Journal of Optimization and Control: Theories & Applications, 2025, 15(2): 281-293 DOI:10.36922/ijocta.1678

登录浏览全文

4963

注册一个新账户 忘记密码

Funding

None.

Declaration of competing interest

The authors declare that they have no conflict of interest regarding the publication of this article.

References

[1]

Hernández-Guzmán VM, Orrante-Sakanassi J. PID control of robot manipulators actuated by BLDC motors. Int J Control. 2021; 94(2):267-276. https://doi.org/10.1080/00207179.2019.1590648

[2]

Kuc T-Y., Han W-G. An adaptive PID learning control of robot manipulators. Automatica, 2000; 36(5):717-725. https://doi.org/10.1016/S0005-1098(99)00198-3

[3]

Pan Y, Li X, Yu H. Efficient PID tracking control of robotic manipulators driven by compliant actuators. IEEE Trans Control Syst Technol. 2019; 27(2):915-922. https://doi.org/10.1109/TCST.2017.2783339

[4]

Angel L, Viola J. Fractional order PID for tracking control of a parallel robotic manipulator type delta. ISA Trans. 2018; 79:172-188. https://doi.org/10.1016/j.isatra.2018.04.010

[5]

Sharma R, Gaur P, Mittal AP. Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload. ISA Trans. 2015; 58:279-291. https://doi.org/10.1016/j.isatra.2015.03.013

[6]

Baek J, Jin M, Han S. A New Adaptive Sliding-Mode Control Scheme for Application to Robot Manipulators. IEEE Trans Ind Electron. 2016; 63(6):3628-3637. https://doi.org/10.1109/TIE.2016.2522386

[7]

Kapoor N, Ohri J. Sliding Mode Control (SMC) of Robot Manipulator via Intelligent Controllers. J Inst Eng India Ser B. 2017; 98(1):83-98. https://doi.org/10.1007/s40031-016-0216-x

[8]

Zhao Y, Sheng Y, Liu X. A Novel Finite Time Sliding Mode Control for Robotic Manipulators. IFAC Proc Vol. 2014; 47(3):7336-7341. https://doi.org/10.3182/20140824-6-ZA-1003.00135

[9]

Dumlu A. Practical Position Tracking Control of a Robotic Manipulator Based on Fractional Order Sliding Mode Controller. Elektr Ir Elektrotech. 2018; 24(5):19-25. https://doi.org/10.5755/j01.eie.24.5.21838

[10]

Rahmani M, Rahman MH. Adaptive Neural Network Fast Fractional Sliding Mode Control of a 7-DOF Exoskeleton Robot. Int J Control Autom Syst. 2020; 18(1):124-133. https://doi.org/10.1007/s12555-019-0155-1

[11]

Sachan S, Swarnkar P. Intelligent Fractional Order Sliding Mode Based Control for Surgical Robot Manipulator. Electronics, 2023; 12(3):729. https://doi.org/10.3390/electronics12030729

[12]

Zhang S, Li Z, Wang H, Xiong T. Fractional Order Sliding Mode Control Based on Single Parameter Adaptive Law for Nano-Positioning of Piezoelectric Actuators. IET Control Theory Appl. 2021; 15(10):1422-1437. https://doi.org/10.1049/cth2.12132

[13]

Shah MZ, Samar R, Bhatti AI. Guidance of Air Vehicles: A Sliding Mode Approach. IEEE Trans Control Syst Technol. 2015; 23(1):231-244. https://doi.org/10.1109/TCST.2014.2322773

[14]

Zhao J, Jiang B, Shi P, Liu H. Adaptive Dynamic Sliding Mode Control for Near Space Vehicles Under Actuator Faults. Circ Syst Signal Process. 2013; 32(5):2281-2296. https://doi.org/10.1007/s00034-013-9572-9

[15]

Dokumaci K, Aydemir MT, Salamci MU. Modeling, PID control and simulation of a rocket launcher system. 2014 16th International Power Electronics and Motion Control Conference and Exposition, 2014;1283-1288. Antalya, Turkey. https://doi.org/10.1109/EPEPEMC.2014.6980689

[16]

Muliadi J, Kusumoputro B. Neural Network Control System of UAV Altitude Dynamics and Its Comparison with the PID Control System. J Adv Transp. 2018; 2018(1): 3823201. https://doi.org/10.1155/2018/3823201

[17]

Alagoz BB, Ates A, Yeroglu C. Auto-tuning of PID controller according to fractional-order reference model approximation for DC rotor control. Mechatronics 2013; 23(7):789-797. https://doi.org/10.1016/j.mechatronics.2013.05.001

[18]

Han J, Yu S, Yi S. Adaptive control for robust air flow management in an automotive fuel cell system. Appl Energy. 2017; 190:73-83. https://doi.org/10.1016/j.apenergy.2016.12.115

[19]

Chen K, Astolfi A. Adaptive Control for Systems With Time-Varying Parameters. IEEE Trans Autom Control. 2021; 66(5):1986-2001. https://doi.org/10.1109/TAC.2020.3046141

[20]

Liu Z, Han Z, Zhao Z, He W. Modeling and adaptive control for a spatial flexible spacecraft with unknown actuator failures. Sci China Inf Sci. 2021; 64(5):152208. https://doi.org/10.1007/s11432-020-3109-x

[21]

Tutsoy O, Barkana DE. Model free adaptive control of the under-actuated robot manipulator with the chaotic dynamics. ISA Trans. 2021; 118:106-115. https://doi.org/10.1016/j.isatra.2021.02.006

[22]

Joshua Robert J, Senthil Kumar P, Tushar Nair S, Sharne Moni DH, Swarneswar B. Fuzzy control of active suspension system based on quarter car model. Mater Today Proc. 2022; 66:902-908. https://doi.org/10.1016/j.matpr.2022.04.575

[23]

Kasruddin Nasir AN, Ahmad MA, Tokhi MO. Hybrid spiral-bacterial foraging algorithm for a fuzzy control design of a flexible manipulator. J Low Freq Noise Vibr Act Control 2022; 41(1):340-358. https://doi.org/10.1177/14613484211035646

[24]

Öztürk M, Özkol İ. Comparison of modified Karnik-Mendel algorithm-based interval type-2 ANFIS and type-1 ANFIS. Aircr Eng Aerosp Technol. 2021; 93(10):1526-1532. https://doi.org/10.1108/AEAT-11-2020-0268

[25]

Jha D, Ahmed A, Kumar S, Roy D. Fuzzy-PID and interpolation: a novel synergetic approach to process control. Int J Optim Control Theor Appl. (IJOCTA) 2024; 14(4):355-364. https://doi.org/10.11121/ijocta.1483

[26]

Ammar MB, Chaabene M, Chtourou Z. Artificial Neural Network based control for PV/T panel to track optimum thermal and electrical power. Energy Convers Manag. 2013; 65:372-380. https://doi.org/10.1016/j.enconman.2012.08.003

[27]

Kurt R. Control of system parameters by estimating screw withdrawal strength values of particleboards using artificial neural network-based statistical control charts. J Wood Sci. 2022; 68(1):64. https://doi.org/10.1186/s10086-022-02065-y

[28]

Furat M, Eker İ. Experimental Evaluation of Sliding-Mode Control Techniques. Çukurova Univ Mühendislik Mimarlık Fak Derg. 2016; 27(1):23-37.

[29]

Herrera M, Camacho O, Leiva H, Smith C. An approach of dynamic sliding mode control for chemical processes. J Process Control. 2020; 85:112-120. https://doi.org/10.1016/j.jprocont.2019.11.008

[30]

Lee H, Utkin VI. Chattering suppression methods in sliding mode control systems. Annu Rev Control. 2007; 31(2):179-188. https://doi.org/10.1016/j.arcontrol.2007.08.001

[31]

Pisano A, Usai E. Sliding mode control: A survey with applications in math. Math Comput Simul. 2011; 81(5):954-979. https://doi.org/10.1016/j.matcom.2010.10.003

[32]

Gokyildirim A, Calgan H, Demirtas M. Fractional-Order sliding mode control of a 4D memristive chaotic system. J Vib Control. 2024; 30(7-8):1604-1620. https://doi.org/10.1177/10775463231166187

[33]

Hua C, Chen J, Guan X. Fractional-order sliding mode control of uncertain QUAVs with time-varying state constraints. Nonlinear Dyn. 2019; 95(2):1347-1360. https://doi.org/10.1007/s11071-018-4632-0

[34]

Saif A-WA, Gaufan KB, El-Ferik S, Al-Dhaifallah M. Fractional Order Sliding Mode Control of Quadrotor Based on Fractional Order Model. IEEE Access, 2023; 11:79823-79837. https://doi.org/10.1109/ACCESS.2023.3296644

[35]

Wang J, Shao C, Chen Y-Q. Fractional order sliding mode control via disturbance observer for a class of fractional order systems with mismatched disturbance,. Mechatronics, 2018; 53:8-19. https://doi.org/10.1016/j.mechatronics.2018.05.006

[36]

Moshiri B, Jalili-Kharaajoo M, Besharati F. Application of fuzzy sliding mode based on genetic algorithms to control of robotic manipulators. EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696) 2003;2:169-172 vol. 2. Lisbon, Portugal. https://doi.org/10.1109/ETFA.2003.1248691

[37]

Utkin VI. Variable Structure Systems with Sliding Modes. IEEE Trans Autom Control. 1977; 22(2):212-222.

[38]

Utkin VI. Sliding Modes in Problems of Mathematical Programming. In: Sliding Modes in Control and Optimization. Springer; 1992: 223-236. https://doi.org/10.1007/978-3-642-84379-2_15

[39]

Panchade VM, Chile RH, Patre BM. A survey on sliding mode control strategies for induction motors. Annu Rev Control. 2013; 37(2):289-307. https://doi.org/10.1016/j.arcontrol.2013.09.008

[40]

Tan S-C, Lai Y-M, Tse C-K. Sliding Mode Control of Switching Power Converters: Techniques and Implementation. CRC Press; 2017. https://doi.org/10.1201/9781315217796

[41]

Yan H, Zhang H, Zhan X, Wang Y, Chen S, Yang F. Event-Triggered Sliding Mode Control of Switched Neural Networks With Mode-Dependent Average Dwell Time. IEEE Trans Syst Man Cybern Syst. 2021; 51(2):1233-1243. https://doi.org/10.1109/TSMC.2019.2894984

[42]

Yau H-T, Chen C-L. Chattering-free fuzzy sliding-mode control strategy for uncertain chaotic systems. Chaos, Solitons & Fractals, 2006; 30(3):709-718. https://doi.org/10.1016/j.chaos.2006.03.077

[43]

Basci A, Can K, Orman K, Derdiyok A. Trajectory Tracking Control of a Four Rotor Unmanned Aerial Vehicle Based on Continuous Sliding Mode Controller. Elektr Ir Elektrotech. 2017; 23(3):12-19. https://doi.org/10.5755/j01.eie.23.3.18325

[44]

Haridas V, Vivek A. Longitudinal Guidance of Unmanned Aerial Vehicle Using Integral Sliding Mode Control. Procedia Technol. 2016; 25:36-43. https://doi.org/10.1016/j.protcy.2016.08.078

[45]

Barambones O. Sliding Mode Control Strategy for Wind Turbine Power Maximization. Energies, 2012; 5(7):2310-2330. https://doi.org/10.3390/en5072310

[46]

Firouzi M, Nasiri M, Mobayen S, Gharehpetian GB. Sliding Mode Controller-Based BFCL for Fault Ride-Through Performance Enhancement of DFIG-Based Wind Turbines. Complexity, 2020; 2020(1): 1259539. https://doi.org/10.1155/2020/1259539

[47]

Arisoy A, Bayrakceken MK, Basturk S, Gokasan M, Bogosyan OS. High order sliding mode control of a space robot manipulator. Proceedings of 5th International Conference on Recent Advances in Space Technologies-RAST2011, 2011;833-838. https://doi.org/10.1109/RAST.2011.5966960

[48]

Cai X, Liu F. Numerical simulation of the fractional-order control system. J Appl Math Comput. 2007; 23(1):229-241. https://doi.org/10.1007/BF02831971

[49]

Ma C, Hori Y. Fractional-order control: Theory and applications in motion control [Past and present]. IEEE Ind Electron Mag. 2007; 1(4):6-16. https://doi.org/10.1109/MIE.2007.909703

[50]

Petráš I. Tuning and implementation methods for fractional-order controllers. Fract Calc Appl Anal. 2012; 15(2):282-303. https://doi.org/10.2478/s13540-012-0021-4

[51]

Naik PA, Owolabi KM, Yavuz M, Zu J. Chaotic dynamics of a fractional order HIV-1 model involving AIDS-related cancer cells. Chaos, Solitons & Fractals, 2020;140:110272. https://doi.org/10.1016/j.chaos.2020.110272

[52]

Yavuz M, Bonyah E. New approaches to the fractional dynamics of schistosomiasis disease model. Phys A Stat Mech Its Appl. 2019; 525:373-393. https://doi.org/10.1016/j.physa.2019.03.069

[53]

Bhatter S, Kumawat S, Bhatia B, Purohit SD. Analysis of COVID-19 epidemic with intervention impacts by a fractional operator. Int J Optim Control Theor Appl. (IJOCTA) 2024; 14(3):261-275. https://doi.org/10.11121/ijocta.1515

[54]

Yavuz M, Yaşkıran B. Approximate-analytical solutions of cable equation using conformable fractional operator. New Trends Math Sci. 2017; 5(4):209-219.

[55]

Yavuz M, Yaşkıran B. Homotopy methods for fractional linear/nonlinear differential equations with a local derivative operator. Balıkesir Univ Fen Bilim Enst Derg. 2018; 20(3):75-89. https://doi.org/10.25092/baunfbed.476608

[56]

Yépez-Martínez H, Gómez-Aguilar JF. A new modified definition of Caputo-Fabrizio fractional-order derivative and their applications to the Multi Step Homotopy Analysis Method (MHAM). J Comput Appl Math. 2019; 346:247-260. https://doi.org/10.1016/j.cam.2018.07.023

[57]

Zhao C, Xue D, Chen Y. A fractional order PID tuning algorithm for a class of fractional order plants. IEEE Int Conf Mechatron Autom. 2005;2005:1,216-221 Vol. 1. https://doi.org/doi:10.1109/ICMA.2005.1626550

[58]

Zahraoui Y, Zaihidee FM, Kermadi M, et al. Fractional Order Sliding Mode Controller Based on Supervised Machine Learning Techniques for Speed Control of PMSM. Mathematics, 2023; 11(6):1457. https://doi.org/10.3390/math11061457

[59]

Yuvapriya T, Lakshmi P. Simulation study on ride comfort enhancement for a heavy duty vehicle with fractional order sliding mode controller. SN Appl Sci. 2020; 2(9):1478. https://doi.org/10.1007/s42452-020-03263-3

[60]

Nafiz Musarrat M, Fekih A. Fractional Order SMC Design to Enhance the Dynamic Stability of PV Systems During Unexpected Network Events. 2022 American Control Conference (ACC), 2022;2553-2558. https://doi.org/10.23919/ACC53348.2022.9867426

[61]

Beniss MA, El Moussaoui H, Lamhamdi T, El Markhi H. Comparative Study Between FOSMC and SMC Controllers for DFIG Under the Real Wind Profile of Asilah-Morocco City. In: Bennani S, Lakhrissi Y, Khaissidi G, Mansouri A, Khamlichi Y, eds. WITS 2020. Springer; 2022: 673-685. https://doi.org/10.1007/978-981-33-6893-4_62

[62]

Basilio JCC, Oliveira TR, Ribeiro JGT, Cunha A. Evaluation of Fractional-Order Sliding Mode Control Applied to an Energy Harvesting System. 2022 16th International Workshop on Variable Structure Systems (VSS), 2022; 243-248. https://doi.org/10.1109/VSS57184.2022.9902105

[63]

Yavuz M, Öztürk M, Yaşkıran B. Sliding Mode Controller of Fractional Order for a Robot Manipulator Control. In: Jha BK, Jha N, Brahma J, Yavuz M, eds. Computational Modeling and Sustainable Energy. ICCMSE 2023. Innovations in Sustainable Technologies and Computing. Springer; 2025. https://doi.org/10.1007/978-981-97-6794-6_12

[64]

Belhocine M, Hamerlain M, Bouyoucef K. Robot control using a sliding mode. Proceedings of 12th IEEE International Symposium on Intelligent Control, 1997;361-366. Istanbul, Turkey. https://doi.org/10.1109/ISIC.1997.626506

[65]

Utkin VI. Sliding mode control design principles and applications to electric drives. IEEE Trans Ind Electron. 1993; 40(1):23-36.

[66]

Giap V, Vu H, Nguyen Q, Huang S-C. Chattering-Free Sliding Mode Control-Based Disturbance Observer for Mems Gyroscope System. Microsyst Technol. 2022; 28(8):1867-1877.

[67]

Podlubny I ed. Chapter 2—Fractional Derivatives and Integrals. In: Mathematics in Science and Engineering. Elsevier; 1999: 41-119. https://doi.org/10.1016/S0076-5392(99)80021-6

[68]

Zhang X, Xu W, Lu W. Fractional-order iterative sliding mode control based on the neural network for manipulator. Math Probl Eng. 2021; 2021(1): 9996719. https://doi.org/10.1155/2021/9996719

[69]

Islam MR, Rahmani M, Rahman MH. A novel exoskeleton with fractional sliding mode control for upper limb rehabilitation. Robotica, 2020; 38(11):2099-2120. https://doi.org/10.1017/S0263574719001851

PDF (2404KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/