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article

MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

Authors:

Tzuu-Hseng S. Li,

Yun-Cheng HuangAuthors Info & Claims

Information Sciences—Informatics and Computer Science, Intelligent Systems, Applications: An International Journal, Volume 180, Issue 23

Pages 4641 - 4660

https://doi.org/10.1016/j.ins.2010.08.009

Published: 01 December 2010 Publication History

Abstract

A new design approach of a multiple-input-multiple-output (MIMO) adaptive fuzzy terminal sliding-mode controller (AFTSMC) for robotic manipulators is described in this article. A terminal sliding-mode controller (TSMC) can drive system tracking error to converge to zero in finite time. The AFTSMC, incorporating the fuzzy logic controller (FLC), the TSMC, and an adaptive scheme, is designed to retain the advantages of the TSMC while reducing the chattering. The adaptive law is designed on the basis of the Lyapunov stability criterion. The self-tuning parameters are adapted online to improve the performance of the fuzzy terminal sliding-mode controller (FTSMC). Thus, it does not require detailed system parameters for the presented AFTSMC. The simulation results demonstrate that the MIMO AFTSMC can provide a reasonable tracking performance.

References

[1]

}}Barai, R.K. and Nonami, K., Optimal two-degree-of-freedom fuzzy control for locomotion control of a hydraulically actuated hexapod robot. Information Sciences. v177. 1892-1915.

Digital Library

[2]

}}Chen, C.-S., Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems. Information Sciences. v179. 2676-2688.

Digital Library

[3]

}}Chen, C.-Y., Li, T.-H.S. and Yeh, Y.-C., EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots. Information Sciences. v179. 180-195.

Digital Library

[4]

}}Da, F. and Song, W., Fuzzy neural networks for direct adaptive control. IEEE Transactions Industrial Electronics. v11 i6. 1471-1480.

[5]

}}Deshpande, P.B. and Ash, R.H., Computer Process Control with Advanced Control Applications. 1988. second ed. Instrument Society of America, North Carolina.

[6]

}}Echanobe, J., del Campo, I. and Bosque, G., An adaptive neuro-fuzzy system for efficient implementations. Information Sciences. v178. 2150-2162.

[7]

}}Feng, Y., Yu, X. and Man, Z., Non-singular terminal sliding-mode control of rigid manipulators. Automatica. v38. 2159-2167.

Digital Library

[8]

}}Guo, Y. and Woo, P.-Y., An adaptive fuzzy sliding-mode controller for robotic manipulators. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. v33 i2. 149-159.

[9]

}}Ho, H.F., Wong, Y.K. and Rad, A.B., Robust fuzzy tracking control for robotic manipulators. Simulation Modelling Practice and Theory. v15. 801-816.

[10]

}}Hsiao, M.-Y., Li, T.-H.S., Lee, J.-Z., Chao, C.-H. and Tsai, S.-H., Design of interval type-2 fuzzy sliding-mode controller. Information Sciences. v178. 1696-1716.

Digital Library

[11]

}}Hsu, Y.-C., Chen, G. and Li, H.-X., A fuzzy adaptive variable structure controller with applications to robotic manipulators. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. v31 i3. 331-340.

[12]

}}Huang, Y.-J., Kuo, T.-C. and Chang, S.-H., Adaptive sliding-mode control for nonlinear systems with uncertain parameters. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. v38 i2. 534-539.

[13]

}}Huang, D. and Nguang, S.K., Static output feedback controller design for fuzzy systems: an ILMI approach. Information Sciences. v177. 3005-3015.

Digital Library

[14]

}}Hung, J.Y., Gao, W. and Huang, J.C., Variable structure control: a survey. IEEE Transactions Industrial Electronics. v40 i1. 2-22.

[15]

}}Janardhanan, S. and Bandyopadhyay, B., On discretization of continuous-time terminal sliding-mode. IEEE Transactions on Automatic Control. v51 i9. 1532-1536.

[16]

}}Kim, T.W. and Yuh, J., Application of on-line neuro-fuzzy controller to AUVs. Information Sciences. v145. 169-182.

[17]

}}Kuo, C.-L., Li, T.-H.S. and Guo, N.R., Design of a novel fuzzy sliding-mode control for magnetic ball levitation system. Journal of Intelligent and Robotic Systems. v42 i3. 295-316.

[18]

}}Li, T.-H.S., Hsiao, M.-Y., Lee, J.-Z. and Tsai, S.-H., Controlling a time-varying unified chaotic system via interval type 2 fuzzy sliding-mode technique. International Journal of Nonlinear Sciences and Numerical Simulation. v10 i2. 171-180.

[19]

}}Li, T.-H.S., Lee, J.-Z., Hsiao, M.-Y. and Tsai, S.-H., Robust interval fuzzy control of a class of uncertain chaotic system. International Journal of Nonlinear Sciences and Numerical Simulation. v10 i2. 81-190.

[20]

}}Li, J.-H., Li, T.-H.S. and Ou, T.-H., Design and implementation of fuzzy sliding-mode controller for a wedge balancing system. Journal of Intelligent and Robotic Systems. v37 i3. 285-306.

[21]

}}Li, T.-H.S. and Lin, K.-J., Stabilization of singularly perturbed fuzzy systems. IEEE Transactions on Fuzzy Systems. v12 i5. 579-595.

[22]

}}Li, T.-H.S., Tsai, S.-H. and Hsiao, M.-Y., Robust fuzzy control for a class of time-delay fuzzy bilinear systems with an additive disturbance. International Journal of Nonlinear Sciences and Numerical Simulation. v10 i3. 315-322.

[23]

}}Lian, K.-Y., Su, C.-H. and Huang, C.-S., Performance enhancement for T-S fuzzy control using neural networks. IEEE Transactions on Fuzzy Systems. v14 i5. 619-627.

[24]

}}Liang, Y.-W., Xu, S.-D., Liaw, D.-C. and Chen, C.-C., A study of T-S model-based SMC scheme with application to robot control. IEEE Transactions on Industrial Electronics. v55 i11. 3964-3971.

[25]

}}Lin, C.-K., Nonsingular terminal sliding-mode control of robot manipulators using fuzzy wavelet networks. IEEE Transactions on Fuzzy Systems. v14 i6. 849-859.

[26]

}}Lin, C.-K., Robust adaptive critic control of nonlinear systems using fuzzy basis function networks: an LMI approach. Information Sciences. v177. 4934-4946.

[27]

}}Liu, Y.-J. and Wang, W., Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems. Information Sciences. v177. 3901-3917.

Digital Library

[28]

}}Lopez-Juarez, I., Corona-Castuera, J., Pena-Cabrera, M. and Ordaz-Hernandez, K., On the design of intelligent robotic agents for assembly. Information Sciences. v171. 377-402.

[29]

}}Mansouri, B., Manamanni, N., Guelton, K., Kruszewski, A. and Guerra, T.M., Output feedback LMI tracking control conditions with H∞ criterion for uncertain and disturbed T-S models. Information Sciences. v179. 446-457.

[30]

}}Mbede, J.B., Ele, P., Mveh-Abia, C.-M., Toure, Y., Graefe, V. and Ma, S., Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems. Information Sciences. v171. 447-474.

[31]

}}Pedrycz, W., Why triangular membership functions. Fuzzy Sets and Systems. v64. 21-30.

Digital Library

[32]

}}Pedrycz, W., Fuzzy equalization in the construction of fuzzy sets. Fuzzy Sets and Systems. v119. 329-335.

Digital Library

[33]

}}Pedrycz, W. and Gomide, F., An Introduction to Fuzzy Sets: Analysis and Design. 1998. MIT Press, Cambridge, MA.

[34]

}}Pedrycz, W. and Valente de Oliveira, J., A development of fuzzy encoding and decoding through fuzzy clustering. IEEE Transactions on Instrumentation and Measurement. v57 i4. 829-837.

[35]

}}Precup, R.-E. and Preitl, S., PI-fuzzy controllers for integral plants to ensure robust stability. Information Sciences. v177. 4410-4429.

Digital Library

[36]

}}Sanchez, E.N., Becerra, H.M. and Velez, C.M., Combining fuzzy PID and regulation control for an autonomous mini-helicopter. Information Sciences. v177. 1999-2022.

Digital Library

[37]

}}Roopaei, M. and Jahromi, M.Z., Chattering-free fuzzy sliding-mode control in MIMO uncertain systems. Nonlinear Analysis. v71. 4430-4437.

[38]

}}Sepu'lveda, R., Castillo, O., Melin, P., Dı'az, A.R. and Montiel, O., Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic. Information Sciences. v177. 2023-2048.

[39]

}}Slotine, J.J.E. and Li, W., Applied Nonlinear Control. 1991. Prentice-Hall, Englewood Cliffs, NJ.

[40]

}}Sun, M., Ge, S.S. and Mareels, I.M.Y., Adaptive repetitive learning control of robotic manipulators without the requirement for initial repositioning. IEEE Transactions on Robotics. v22 i3. 563-568.

[41]

}}Tao, C.W., Taur, J.S. and Chan, M.-L., Adaptive fuzzy terminal sliding-mode controller for linear systems with mismatched time-varying uncertainties. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. v34 i1. 255-262.

[42]

}}Ting, C.-S., An observer-based approach to controlling time-delay chaotic systems via Takagi-Sugeno fuzzy model. Information Sciences. v177. 4314-4328.

Digital Library

[43]

}}Tong, S., Li, Y. and Shi, P., Fuzzy adaptive backstepping robust control for SISO nonlinear system with dynamic uncertainties. Information Sciences. v179. 1319-1332.

Digital Library

[44]

}}Wang, L., Chai, T. and Zhai, L., Neural-network-based terminal sliding-mode control of robotic manipulators including actuator dynamics. IEEE Transactions on Industrial Electronics. v56 i9. 3296-3304.

[45]

}}Wong, L.K., Leung, F.H.F. and Tam, P.K.S., A fuzzy sliding controller for nonlinear systems. IEEE Transactions on Industrial Electronics. v48 i1. 32-37.

[46]

}}Yagiz, N., Hacioglu, Y. and Taskin, Y., Fuzzy sliding-mode control of active suspensions. IEEE Transactions on Industrial Electronics. v55 i11. 3883-3890.

[47]

}}Yoneyama, J., Robust stability and stabilizing controller design of fuzzy systems with discrete and distributed delays. Information Sciences. v178. 1935-1947.

Digital Library

[48]

}}Yoo, S.-J., Park, J.-B. and Choi, Y.-H., Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics. v36 i6. 1342-1355.

[49]

}}Yu, X.H. and Zhihong, M., Fast terminal sliding-mode control design for nonlinear dynamical systems. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications. v49 i2. 261-264.

[50]

}}Zadeh, L.A., Toward a generalized theory of uncertainty (GTU) - an outline. Information Sciences. v172. 1-40.

Digital Library

[51]

}}Zadeh, L.A., Is there a need for fuzzy logic. Information Sciences. v178. 2751-2779.

Digital Library

[52]

}}Zhihong, M., Paplinski, A.P. and Wu, H.R., A robust MIMO terminal sliding-mode control scheme for rigid robotic manipulators. IEEE Transactions on Automatic Control. v39 i12. 2464-2469.

[53]

}}Zhihong, M. and Yu, X.H., Terminal sliding-mode control of MIMO linear systems. IEEE Transactions on Circuits and Systems I. v44 i11. 1065-1070.

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Lin J(2022)Adaptive Fixed-Time Constraint Control for Human-Robot Interaction with Uncertainties using Neural NetworksProceedings of the 6th International Conference on Control Engineering and Artificial Intelligence10.1145/3522749.3522750(1-6)Online publication date: 11-Mar-2022
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Van Nguyen THa CTran HLam DCuc N(2022)A Robust Position Tracking Strategy for Robot Manipulators Using Adaptive Second Order Sliding Mode Algorithm and Nonsingular Sliding Mode ControlIntelligent Computing Methodologies10.1007/978-3-031-13832-4_45(544-554)Online publication date: 7-Aug-2022
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Zhang ZYu XGong J(2021)Non-singular Fast Terminal Sliding Mode Fuzzy Adaptive Control of Floating-Based Three-Link Space-Robot with Dead-ZoneIntelligent Robotics and Applications10.1007/978-3-030-89092-6_32(347-359)Online publication date: 22-Oct-2021
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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 180, Issue 23

December, 2010

279 pages

ISSN:0020-0255

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Copyright © Elsevier Inc. © 2010.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 December 2010

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Cited By

Lin J(2022)Adaptive Fixed-Time Constraint Control for Human-Robot Interaction with Uncertainties using Neural NetworksProceedings of the 6th International Conference on Control Engineering and Artificial Intelligence10.1145/3522749.3522750(1-6)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1145/3522749.3522750
Van Nguyen THa CTran HLam DCuc N(2022)A Robust Position Tracking Strategy for Robot Manipulators Using Adaptive Second Order Sliding Mode Algorithm and Nonsingular Sliding Mode ControlIntelligent Computing Methodologies10.1007/978-3-031-13832-4_45(544-554)Online publication date: 7-Aug-2022
https://dl.acm.org/doi/10.1007/978-3-031-13832-4_45
Zhang ZYu XGong J(2021)Non-singular Fast Terminal Sliding Mode Fuzzy Adaptive Control of Floating-Based Three-Link Space-Robot with Dead-ZoneIntelligent Robotics and Applications10.1007/978-3-030-89092-6_32(347-359)Online publication date: 22-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-89092-6_32
Nguyen VLe PKang H(2021)Model-Free Continuous Fuzzy Terminal Sliding Mode Control for Second-Order Nonlinear SystemsIntelligent Computing Theories and Application10.1007/978-3-030-84529-2_21(245-258)Online publication date: 12-Aug-2021
https://dl.acm.org/doi/10.1007/978-3-030-84529-2_21
Dachang ZBaolin DPuchen ZShouyan C(2020)Constant Force PID Control for Robotic Manipulator Based on Fuzzy Neural Network AlgorithmComplexity10.1155/2020/34918452020Online publication date: 1-Jan-2020
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Hu CWang RYan FHuang YWang HWei C(2018)Differential Steering Based Yaw Stabilization Using ISMC for Independently Actuated Electric VehiclesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2017.275006319:2(627-638)Online publication date: 1-Feb-2018
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Khajeh Talkhoncheh MShahrokhi MAskari M(2017)Observer-Based adaptive neural network controller for uncertain nonlinear systems with unknown control directions subject to input time delay and saturationInformation Sciences: an International Journal10.1016/j.ins.2017.08.024418:C(717-737)Online publication date: 1-Dec-2017
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Wu TKarkoub MYu WChen CHer MWu K(2016)Anti-sway tracking control of tower cranes with delayed uncertainty using a robust adaptive fuzzy controlFuzzy Sets and Systems10.1016/j.fss.2015.01.010290:C(118-137)Online publication date: 1-May-2016
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Yang YHua CGuan X(2015)Finite-time synchronization control for bilateral teleoperation under communication delaysRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2014.07.00131:C(61-69)Online publication date: 1-Feb-2015
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Mon YLin C(2014)3-Dimensional sliding mode adaptive MIMO recurrent fuzzy neural network control for two-link manipulator systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.5555/3184235.318425827:3(1325-1334)Online publication date: 1-May-2014
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