nach oben

Neural Computing and Applications

Erschienen in:

03.01.2021 | Original Article

Control of twin-double pendulum lower extremity exoskeleton system with fuzzy logic control method

verfasst von: A. K. Tanyildizi, O. Yakut, B. Taşar, A. B. Tatar

Erschienen in: Neural Computing and Applications | Ausgabe 13/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In this article, a two degree of freedom lower-limb exoskeleton (LLE) design control is developed to reduce the fatigue level of healthy people and increase their load-carrying capacity. The LLE robot system is designed by comparing it to the twin-double pendulum system. One of the twin pendulums models is the human leg (with a knee and hip joint), and the other twin pendulum model is the exoskeleton robot. The movement of the human knee and hip joints in a walking pattern is recreated with a joint angle generator and applied to the joints with the help of a linear motor. The exoskeleton robot is provided to follow the movements of the leg with the help of a fuzzy controller. The control simulation with the mathematical model of the twin-double pendulum system and the fuzzy logic method was made using the MATLAB/Simulink program. The system response was analyzed and graphed for two different limb sizes (45 cm and 50 cm) and three different load conditions (no load, 25 Nm and 75 Nm). The maximum tracking errors are 3.2105° and 3.4730° for the hip and knee joint, respectively, with a 75 Nm load disturbance condition. These tracking error values can be interpreted as very low with high tracking success. The FL controller is robust to load changing and limb size-changing factors, and for this reason, it was suitable for use in LLEs.

Vorheriger Artikel Hybrid signal processing/machine learning and PSO optimization model for conjunctive management of surface–groundwater resources

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Yan T, Cempini M, Oddo CM et al (2015) Review of assistive strategies in powered lower-limb orthoses and exoskeletons. Robot Auton Syst 64:120–136CrossRef

Long Y, Du Z, Chen C, Wang W, Dong W, He L, Mao X, Xu G, Zhao G (2017) Development and analysis of an electrically actuated lower extremity assistive exoskeleton. J Bionic Eng 14:272–283. https://doi.org/10.1016/S1672-6529(16)60397-9CrossRef

Hussain S, Jamwal PK, Ghayesh MH (2016) Joint robotic orthoses for gait rehabilitation: an educational technical review. J Rehabil Med 48:333–338CrossRef

Hussain S, Xie SQ, Jamwal PK (2013) Control of a robotic orthosis for gait rehabilitation. Robot Auton Syst 61:911–919CrossRef

Quy-Thinh D, Shin-ichiroh Y (2018) Assist-as-needed control of a robotic orthosis actuated by pneumatic artificial muscle for gait rehabilitation. Appl Sci 8:499. https://doi.org/10.3390/app8040499CrossRef

Hussain S, Xie SQ, Jamwal PK (2013) Robust nonlinear control of an intrinsically compliant robotic gait training orthosis. IEEE Trans Syst Man Cybern Syst 43:655–665CrossRef

Choi B, Seo C, Lee S, Kim B, Kim D (2017) Swing control of a lower extremity exoskeleton using echo state networks. IFAC PapersOnLine 50(1):1328–1333. https://doi.org/10.1016/j.ifacol.2017.08.220CrossRef

Sunil K, Jagan D, Shaktidev M (2014) Advances in intelligent systems and computing. In: ICT and critical infrastructure: proceedings of the 48th annual convention of computer society of India-Vol II, Hyderabad, Telangana, India, pp 577–583

Dai JS, Zoppi M, Kong X (2012) Advances in reconfigurable mechanisms and robots. Springer, LondonCrossRef

10.

Sun W, Lin J, Su S, Wang N, Er MJ (2020) Reduced adaptive fuzzy decoupling control for lower limb exoskeleton. IEEE Trans Cybern. https://doi.org/10.1109/tcyb.2020.2972582CrossRef

11.

Yang Y, Ma L, Huang DQ (2017) Development and repetitive learning control of lower limb exoskeleton driven by electrohydraulic actuators. IEEE Trans Ind Electron 64(5):4169–4178CrossRef

12.

Chen J, Hochstein J, Kim C, Damiano D, Bulea T (2018) Design advancements toward a wearable pediatric robotic knee exoskeleton for overground gait rehabilitation. In: 2018 7th IEEE international conference on biomedical robotics and biomechatronics (Biorob) Enschede, The Netherlands, August 26–29, 2018

13.

Luo Y, Wang C, Wang Z, Ma Y, Wang C, Wu; X (2017) Design and control for a compliant knee exoskeleton. In: Proceedings of the 2017 IEEE international conference on information and automation (ICIA) Macau SAR, China, July 2017

14.

Zhang X, Yue Z, Wang J Robotics in lower-limb rehabilitation after stroke, Hindawi Behav Neurol Vol 2017, Article ID 3731802, 13. https://doi.org/10.1155/2017/3731802

15.

Wang LJ, Li HY, Zhou Q, Lu RQ (2017) Adaptive fuzzy control for nonstrict feedback systems with unmodeled dynamics and fuzzy dead zone via output feedback. IEEE Trans Cybern 47(9):2400–2412CrossRef

16.

Sun W, Su S, Wu Y, Xia J, Nguyen V (2019) Adaptive fuzzy control with high-order barrier Lyapunov functions for high-order uncertain nonlinear systems with full-state constraints. IEEE Trans Cybern. https://doi.org/10.1109/tcyb.2018.2890256CrossRef

17.

Yin S, Shi P, Yang HY (2016) Adaptive fuzzy control of strict-feedback nonlinear time-delay systems with unmodeled dynamics. IEEE Trans Cybern 46(8):1926–1938CrossRef

18.

Li YM, Tong SC (2017) Adaptive fuzzy output constrained control design for multi-input multioutput stochastic nonstrict-feedback nonlinear systems. IEEE Trans Cybern 47(12):4086–4095CrossRef

19.

Yang Y, Huang D, Dong X (2019) Enhanced neural network control of lower limb rehabilitation exoskeleton by add-on repetitive learning. Neurocomputing 323:256–264. https://doi.org/10.1016/j.neucom.2018.09.085CrossRef

20.

He W, Meng TT, He XY, Ge SS (2018) Unified iterative learning control for flexible structures with input constraints. Automatica 86:326–336MathSciNetCrossRef

21.

Zhao XD, Yang HJ, Karimi HR, Zhu YZ (2016) Adaptive neural control of MIMO nonstrict-feedback nonlinear systems with time delay. IEEE Trans Cybern 46(6):1337–1349CrossRef

22.

Zhao XD, Yang HJ, Xia WG, Wang XY (2017) Adaptive fuzzy hierarchical sliding-mode control for a class of MIMO nonlinear timedelay systems with input saturation. IEEE Trans Fuzzy Syst 25(5):1062–1077CrossRef

23.

Li YM, Tong SC (2017) Command-filtered-based fuzzy adaptive control design for MIMO-switched nonstrict-feedback nonlinear systems. IEEE Trans Fuzzy Syst 25(3):668–681CrossRef

24.

Sun W, Su S-F, Xia J, Wu Y (2018) Adaptive tracking control of wheeled inverted pendulums with periodic disturbances. IEEE Trans Cybern. https://doi.org/10.1109/tcyb.2018.2884707CrossRef

25.

Chen ZT, Li ZJ, Chen CLP (2017) Adaptive neural control of uncertain MIMO nonlinear systems with state and input constraints. IEEE Trans Neural Netw Learn Syst 28(6):1318–1330CrossRef

26.

Song YD, Huang XC, Wen CY (2017) Robust adaptive faulttolerant PID control of MIMO nonlinear systems with unknown control direction. IEEE Trans Ind Electron 64(6):4876–4884CrossRef

27.

Jin X (2017) Adaptive finite-time fault-tolerant tracking control for a class of MIMO nonlinear systems with output constraints. Int J Robust Nonlinear Control 27(5):722–741MathSciNetCrossRef

28.

Mohammadzadeh A, Ghaemi S (2016) A modified sliding mode approach for synchronization of fractional-order chaotic/hyperchaotic systems by using new self-structuring hierarchical type-2 fuzzy neural network. Neurocomputing 191:200–213CrossRef

29.

Young KD, Utkin VI, Özgüner Ü (1999) A control engineer’s guide to sliding mode control. IEEE Trans Control Syst Technol 7(3):328–342CrossRef

30.

Ma Z, Sun G (2016) Adaptive sliding mode control of tethered satellite deployment with input limitation. Acta Astronaut 127:67–75CrossRef

31.

Song YD, Lu Y, Gan ZX (2016) Descriptor sliding mode approach for fault/noise reconstruction and fault-tolerant control of nonlinear uncertain systems. Inf Sci 367–368:194–208CrossRef

32.

Mohammed S, Huo W, Huang J, Rifai H, Amirat Y (2017) Nonlinear disturbance observer-based sliding mode control of a human-driven knee joint orthosis. Robot Auton Syst 75:41–49CrossRef

33.

Teng L, Bai S (2019) Fuzzy sliding mode control of an upper-limb exoskeleton robot. In: 2019 IEEE international conference on cybernetics and intelligent systems (CIS) and IEEE conference on robotics, automation and mechatronics (RAM), Bangkok, Thailand, pp 12–17. https://doi.org/10.1109/cis-ram47153.2019.9095811

34.

Teng L, Wang Y, Cai W, Li H (2018) Fuzzy model predictive control of discrete-time systems with time-varying delay and disturbances. IEEE Trans Fuzzy Syst 26(3):1192–1206CrossRef

35.

Teng L, Wang Y, Cai W, Li H (2018) Robust fuzzy model predictive control of discrete-time Takagi-Sugeno systems with nonlinear local models. IEEE Trans Fuzzy Syst 26(5):2915–2925CrossRef

36.

Teng L, Wang Y, Cai W, Li H (2019) Efficient robust fuzzy model predictive control of discrete nonlinear time-delay systems via Razumikhin approach. IEEE Trans Fuzzy Syst 27(2):262–272CrossRef

37.

Zadeh LA (1965) Fuzzy Sets. Inf Control 8:338–353. https://doi.org/10.1016/S0019-9958(65)90241-XCrossRefMATH

38.

Han J, Yang S, Xia L, Chen Y (2020) Deterministic adaptive robust control with a novel optimal gain design approach for a fuzzy 2DOF lower limb exoskeleton robot system. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/tfuzz.2020.2999739CrossRef

39.

Zhao R, Chen Y-H, Jiao S (2015) Optimal design of constraint-following control for fuzzy mechanical systems. IEEE Trans Fuzzy Syst 24(5):1108–1120CrossRef

40.

Sun H, Zhao H, Huang K, Qiu M, Zhen S, Chen Y-H (2017) A fuzzy approach for optimal robust control design of an automotive electronic throttle system. IEEE Trans Fuzzy Syst 26(2):694–704CrossRef

41.

Xu J, Du Y, Chen Y-H, Guo H (2018) Optimal robust control design for constrained uncertain systems: a fuzzy-set theoretic approach. IEEE Trans Fuzzy Syst 26(6):3494–3505CrossRef

42.

Wu Q, Wang X, Du F, Zhang X (2015) Design and control of a powered hip exoskeleton for walking assistance. Int J Adv Robot Syst 12(3):18CrossRef

43.

Ning Donghong, Sun Shuaishuai, Zhang Fei, Haiping Du, Li Weihua, Zhang Bangji (2017) Disturbance observer based takagi-sugeno fuzzy control for an active seat suspension. Mech Syst Signal Process 93:515–530CrossRef

44.

Zhang Zhenxing, Liang Hongjing, Ma Hui, Pan Yingnan (2019) Reliable fuzzy control for uncertain vehicle suspension systems with random incomplete transmission signals and sensor failure. Mech Syst Signal Process 130:776–789CrossRef

45.

Chen Jian, Chenfeng Xu, Chengshuai Wu, Weihua Xu (2016) Adaptive fuzzy logic control of fuel-cell-battery hybrid systems for electric vehicles. IEEE Trans Industr Inf 14(1):292–300CrossRef

46.

Yang S, Han J, Xia L, Chen Y-H (2020) An optimal fuzzy-theoretic setting of adaptive robust control design for a lower limb exoskeleton robot system. Mech Syst Signal Process 141:106706. https://doi.org/10.1016/j.ymssp.2020.106706CrossRef

47.

Anwara T, Al Juamily A (2014) Adaptive trajectory control to achieve smooth interaction force in robotic rehabilitation device. Procedia Comput Sci 42:160–167, International conference on robot PRIDE 2013–2014—medical and rehabilitation robotics and instrumentation

48.

Bingül Z, Og˘uzhan K (2011) A fuzzy logic controller tuned with PSO for 2 DOF robot trajectory control. Expert Syst Appl 38:1017–1031CrossRef

49.

Jamwal PK, Xie SQ, Member S, Hussain S, Parsons JG (2014) An adaptive wearable parallel robot for the treatment of ankle injuries. IEEE/ASME Trans Mech 19(1)

50.

Zhong C-H, Zhao X, Liang F-Y, Ma H, Liao W-H (2019) Motion adaption and trajectory generation of stair ascent and descent with a lower limb exoskeleton for paraplegics. In: Proceedings of the 2019 IEEE/ASME international conference on advanced intelligent mechatronics Hong Kong, China, July 8–12

51.

Chen C et al (2019) Development and hybrid control of an electrically actuated lower limb exoskeleton for motion assistance. IEEE Access 7:169107–169122. https://doi.org/10.1109/ACCESS.2019.2953302CrossRef

52.

Sun W, Lin J, Su S, Wang N, Er MJ (2020) Reduced adaptive fuzzy decoupling control for lower limb exoskeleton. IEEE Trans Cybern. https://doi.org/10.1109/tcyb.2020.2972582CrossRef

53.

Amin A, Tahamipour-Z SM, Akbarzadeh A (2019) Adaptive tracking control based on GFHM for a reconfigurable lower limb exoskeleton. In: 2019 7th international conference on robotics and mechatronics (ICRoM), pp 74–79

54.

55.

Zhang X, Li J, Ovur SE, Chen Z, Li X, Hu Z, Hu Y (2020) Novel design and adaptive fuzzy control of a lower-limb elderly rehabilitation. Electronics 9:343CrossRef

56.

Rıfai H, Mohammed S, Djouani K, Amirat Y (2017) Toward lower limbs functional rehabilitation through a knee-joint exoskeleton. IEEE Trans Control Syst Technol 25(2):712–719. https://doi.org/10.1109/TCST.2016.2565385CrossRef

57.

McGibbon CA, Brandon SCE, Brookshaw M, Sexton A (2017) Effects of an over-ground exoskeleton on external knee moments during the stance phase of gait in healthy adults. Knee 24:977–993. https://doi.org/10.1016/j.knee.2017.04.004CrossRef

58.

Wang J, Li X, Huang TH, Yu S, Li Y, Chen T, Carriero A, Park MO, Su H (2018) Comfort-centered design of a lightweight and backdrivable knee exoskeleton. IEEE Robot Autom Lett 3(4):4265–4272. https://doi.org/10.1109/LRA.2018.2864352CrossRef

59.

Alamir M, Murilo A (2008) Swing-up and stabilization of a twin-pendulum under state and control constraints by a fast NMPC scheme. Automatica 44:1319–1324. https://doi.org/10.1016/j.automatica.2007.09.020MathSciNetCrossRefMATH

60.

Pinto AMA, Alamir M (2007) Output feedback design of a twin pendulum system in presence of sensor bias. IFAC Proc 40(12):1167–1172. https://doi.org/10.3182/20070822-3-ZA-2920.00193CrossRef

61.

Sankai Y (2006) Leading edge of cybernics: robot suit HAL. In: Proceedings of international joint conference SICE-ICASE, 2006, pp P-1–P-2

62.

Huo W, Mohammed S, Moreno JC, Amirat Y (2016) Lower limb wearable robots for assistance and rehabilitation: a state of the art. IEEE Syst J 10(3):1068–1081CrossRef

63.

Veale AJ, Xie SQ (2016) Towards compliant and wearable robotic orthoses: a review of current and emerging actuator technologies. Med Eng Phys 38(4):317–325. https://doi.org/10.1016/j.medengphy.2016.01.010CrossRef

64.

Banala SK, Kim SH, Agrawal SK, Scholz JP (2018) Robot-assisted gait training with active leg exoskeleton (ALEX). IEEE Trans Neural Syst Rehabil Eng 17:2–8. https://doi.org/10.1109/TNSRE.2008.2008280CrossRef

65.

Srivastava S, Kao PC, Kim SH, Stegall P, Zanotto D, Higginson JS, Agrawal SK, Scholz JP (2015) Assist-as-needed robot-aided gait training improves walking function in individuals following stroke. IEEE Trans Neural Syst Rehabil Eng 23:956–963. https://doi.org/10.1109/TNSRE.2014.2360822CrossRef

66.

Chu A, Kazeroni H, Zoss A (2005) On the biomimetic design of the berkeley lower extremity exoskeleton (BLEEX). Int Conf Robot Autom Barc. https://doi.org/10.1109/ROBOT.2005.1570789CrossRef

67.

Fastest Musculoskeletal Insight Engine, Normal gait. https://musculoskeletalkey.com/normal-gait/ (21.07.2020)

68.

Lanbaran NM, Celik E, Yi˘gider M (2020) Evaluation of investment opportunities with interval-valued fuzzy topsis method. Appl Math Nonlinear Sci 5(1):461–474MathSciNetCrossRef

69.

Çitil HG (2019) Investigation of a fuzzy problem by the fuzzy laplace transform. Appl Math Nonlinear Sci 4(2):407–416MathSciNetCrossRef

70.

Hussain S (2014) State-of-the-art robotic gait rehabilitation orthoses: design and control aspects. NeuroRehabilitation 35:701–709CrossRef

Titel: Control of twin-double pendulum lower extremity exoskeleton system with fuzzy logic control method
verfasst von: A. K. Tanyildizi
O. Yakut
B. Taşar
A. B. Tatar
Publikationsdatum: 03.01.2021
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 13/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-020-05554-7

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 13/2021

Improved adaptive neuro-fuzzy inference system based on modified glowworm swarm and differential evolution optimization algorithm for medical diagnosis

Neural computing and applications (NCAA) special issue on best of DICTA 2019 papers

Fixed-Lens camera setup and calibrated image registration for multifocus multiview 3D reconstruction

Exploiting heterogeneity in operational neural networks by synaptic plasticity

Adaptive online prediction of operator position in teleoperation with unknown time-varying delay: simulation and experiments

Hybrid signal processing/machine learning and PSO optimization model for conjunctive management of surface–groundwater resources

Premium Partner