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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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
Armstrong, B., de Wit, C.C.: Friction modeling and compensation. The Control Handbook 77, 1369–1382 (1996)
Benosman, M., Vey, G.L.: Control of flexible manipulators: A survey. Robotica 22(5), 533–545 (2004). doi:10.1017/S0263574703005642
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)
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)
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)
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)
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
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)
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
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)
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
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)
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
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
Kim, E.: Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic. IEEE Trans. Fuzzy Syst. 12, 368–378 (2004)
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
Lin, C.T., Lee, C.S.G.: Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Prentice Hall (1996)
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)
Mendel, J.M.: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall (2001)
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
Olsson, H., Astrom, K., Wit, C.D., Gafvert, M., Lischinsky, P.: Friction models and friction compensation. Eur J. Control 4(3), 176–195 (1998)
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)
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)
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
Pedryez, W.: Why triangular membership functions? Fuzzy Sets Syst. 64(1), 21–30 (1994) doi:10.1016/0165-0114(94)90003-5
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
de Silva, C.W.: Intelligent Control Fuzzy Logic Applications. CRC Press (1995)
Spong, M.W.: Modeling and control of elastic joint robots. J. Dyn. Syst. Meas. Control ASME 109(4), 310–319 (1987)
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
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
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)
Wang, L.X.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis. PTR Prentice Hall (1994)
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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