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Type-2 Fuzzy Logic Control of a Flexible-Joint Manipulator

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Abstract

A type-2 fuzzy logic controller (FLC) is proposed in this article for robot manipulators with joint elasticity and structured and unstructured dynamical uncertainties. The proposed controller is based on a sliding mode control strategy. To enhance its real-time performance, simplified interval fuzzy sets are used. The efficiency of the control scheme is further enhanced by using computationally inexpensive input signals independently of the noisy torque and acceleration signals, and by adopting a trade off strategy between the manipulator’s position and the actuators’ internal stability. The controller is validated through a set of numerical experiments and by comparing it against its type-1 counterpart. It is shown through these experiments the higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities.

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References

  1. Al-Ashoor, R., Patel, R., Khorasani, K.: Robust adaptive controller design and stability analysis for flexible-joint manipulators. IEEE Trans. Syst. Man Cybern. 23(2), 589–602 (1993). doi:10.1109/21.229473

    Article  MATH  Google Scholar 

  2. Armstrong, B., de Wit, C.C.: Friction modeling and compensation. The Control Handbook 77, 1369–1382 (1996)

    Google Scholar 

  3. Benosman, M., Vey, G.L.: Control of flexible manipulators: A survey. Robotica 22(5), 533–545 (2004). doi:10.1017/S0263574703005642

    Article  Google Scholar 

  4. Chaoui, H., Gueaieb, W., Yagoub, M., Sicard, P.: Hybrid neural fuzzy sliding mode control of flexible-joint manipulators with unknown dynamics. In: Proceedings of the 32nd Annual Conference of the IEEE Industrial Electronics Society (IECON-2006), pp. 4082–4087. Paris, France (2006)

  5. Chaoui, H., Sicard, P., Lakhsasi, A.: Reference model supervisory loop for neural network based adaptive control of a flexible joint with hard nonlinearities. In: IEEE Canadian Conference on Electrical and Computer Engineering, vol. 4, pp. 2029–2034. Niagara Falls, Canada (2004)

  6. Chaoui, H., Sicard, P., Lakhsasi, A., Schwartz, H.: Neural network based model reference adaptive control structure for a flexible joint with hard nonlinearities. In: IEEE International Symposium on Industrial Electronics, vol. 1, pp. 271–276 (2004)

  7. Ge, S.S., Postlethwaite, I.: Adaptive neural network controller design for flexible joint robots using singular perturbation technique. Trans. Inst. Meas. Control 17(3), 120–131 (1995)

    Google Scholar 

  8. Ghorbel, F., Spong, M.W.: Adaptive integral manifold control of flexible joint robot manipulators. In: Proceedings – IEEE International Conference on Robotics and Automation, vol. 1, pp. 707–714. Nice, France (1992). doi:10.1109/ROBOT.1992.220285

  9. Gueaieb, W., Karray, F., Al-Sharhan, S.: A robust adaptive fuzzy position/force control scheme for cooperative manipulators. IEEE Trans. Control Syst. Technol. 11(4), 516–528 (2003)

    Article  Google Scholar 

  10. Hagras, H.A.: A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004). doi:10.1109/TFUZZ.2004.832538

    Article  Google Scholar 

  11. Huang, L., Ge, S., Lee, T.: Adaptive position/force control of an uncertain constrained flexible joint robots – singular perturbation approach. In: Proceedings of the SICE Annual Conference, pp. 1693–1698. Sapporo, Japan (2004)

  12. Hui, D., Fuchun, S., Zengqi, S.: Observer-based adaptive controller design of flexible manipulators using time-delay neuro-fuzzy networks. J. Intell. Robot. Syst.: Theory and Applications 34(4), 453–466 (2002). doi:10.1023/A:1019629321735

    Article  MATH  Google Scholar 

  13. Karray, F., Gueaieb, W., Al-Sharhan, S.: The hierarchical expert tuning of PID controllers using tools of soft computing. IEEE Trans. Syst. Man Cybern. 32(1), 77–90 (2002)

    Article  Google Scholar 

  14. Karray, F., de Silva, C.W.: Soft Computing and Intelligent Systems Design, Theory, Tools and Applications. Addison-Wesley, Pearson Education Limited, Essex, England (2004), http://pami.uwaterloo.ca/soft_comp/textbook.html

    Google Scholar 

  15. Khorasani, K.: Nonlinear feedback control of flexible joint manipulators: A single link case study. IEEE Trans. Automat. Contr. 35(10), 1145–1149 (1990). doi:10.1109/9.58558

    Article  MATH  MathSciNet  Google Scholar 

  16. Kim, E.: Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic. IEEE Trans. Fuzzy Syst. 12, 368–378 (2004)

    Article  Google Scholar 

  17. Liang, Q., Mendel, J.M.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5), 535–550 (2000). doi:10.1109/91.873577

    Article  Google Scholar 

  18. Lin, C.T., Lee, C.S.G.: Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Prentice Hall (1996)

  19. Luca, A.D., Isidori, A., Nicolo, F.: Control of robot arm with elastic joints via nonlinear dynamic feedback. In: Proceedings of the IEEE Conference on Decision and Control Including the Symposium on Adaptive Pro, pp. 1671–1679. Fort Lauderdale, FL, USA (1985)

  20. Mendel, J.M.: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall (2001)

  21. Mendel, J.M., John, R.I.B.: Type-2 fuzzy sets made simple. IEEE Trans. Fuzzy Syst. 10(2), 117–127 (2002). doi:10.1109/91.995115

    Article  Google Scholar 

  22. Olsson, H., Astrom, K., Wit, C.D., Gafvert, M., Lischinsky, P.: Friction models and friction compensation. Eur J. Control 4(3), 176–195 (1998)

    MATH  Google Scholar 

  23. Ott, C., Albu-Schaffer, A., Hirzinger, G.: Comparison of adaptive and nonadaptive tracking control laws for a flexible joint manipulator. In: IEEE International Conference on Intelligent Robots and Systems, vol. 2, pp. 2018–2024. Lausanne, Switzerland (2002)

  24. Ott, C., Albu-Schaffer, A., Kugi, A., Stramigioli, S., Hirzinger, G.: A passivity based cartesian impedance controller for flexible joint robots – Part I: Torque feedback and gravity compensation. In: Proceedings – IEEE International Conference on Robotics and Automation, vol. 3, pp. 2659–2665. New Orleans, LA, USA (2004)

  25. Park, C.W.: Robust stable fuzzy control via fuzzy modeling and feedback linearization with its applications to controlling uncertain single-link flexible joint manipulators. J. Intell. Robot. Syst.: Theory and Applications 39(2), 131–147 (2004). doi:10.1023/B:JINT.0000015344.84152.dd

    Article  Google Scholar 

  26. Pedryez, W.: Why triangular membership functions? Fuzzy Sets Syst. 64(1), 21–30 (1994) doi:10.1016/0165-0114(94)90003-5

    Article  Google Scholar 

  27. Seidl, D.R., Lam, S.L., Putman, J.A., Lorenz, R.D.: Neural network compensation of gear backlash hysteresis in position-controlled mechanisms. IEEE Trans. Ind. Appl. 31(6), 1475–1483 (1995). doi:10.1109/28.475744

    Article  Google Scholar 

  28. de Silva, C.W.: Intelligent Control Fuzzy Logic Applications. CRC Press (1995)

  29. Spong, M.W.: Modeling and control of elastic joint robots. J. Dyn. Syst. Meas. Control ASME 109(4), 310–319 (1987)

    Article  MATH  Google Scholar 

  30. Subudhi, B., Morris, A.: Singular perturbation based neuro-h infinity control scheme for a manipulator with flexible links and joints. Robotica 24(2), 151–161 (2006). doi:10.1017/S0263574705001852

    Article  Google Scholar 

  31. Taghirad, H., Khosravi, M.: Design and simulation of robust composite controllers for flexible joint robots. In: Proceedings – IEEE International Conference on Robotics and Automation, vol. 3, pp. 3108–3113. Taipei, Taiwan (2003). doi:10.1109/ROBOT.2003.1242068

  32. Tian, L., Goldenberg, A.: Robust adaptive control of flexible joint robots with joint torque feedback. In: Proceedings - IEEE International Conference on Robotics and Automation, vol. 1, pp. 1229–1234. Nagoya, Jpn (1995)

  33. Wang, L.X.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis. PTR Prentice Hall (1994)

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Authors and Affiliations

  1. Machine Intelligence, Robotics and Mechatronics (MIRaM) Laboratory, School of Information Technology and Engineering (SITE), University of Ottawa, Ottawa, Ontario, Canada

    Hicham Chaoui & Wail Gueaieb

Authors
  1. Hicham Chaoui
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  2. Wail Gueaieb
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Correspondence to Wail Gueaieb.

Additional information

This work was partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Microelectronics Corporation (CMC).

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Chaoui, H., Gueaieb, W. Type-2 Fuzzy Logic Control of a Flexible-Joint Manipulator. J Intell Robot Syst 51, 159–186 (2008). https://doi.org/10.1007/s10846-007-9185-2

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  • DOI: https://doi.org/10.1007/s10846-007-9185-2

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