You are here

ADAPTIVE FUZZY SLIDING MODE CONTROL FOR A CLASS OF BIPARTITE MODULAR ROBOTIC SYSTEMS

Journal Name:

Publication Year:

Abstract (2. Language): 
One of the fundamental issues in the field of modular robotics is the design and implementation of robotic systems with low cost and high performance. Although the coordination of modules entails the minimization of several different performance criteria, the success of the evolution of a group of the modules is strictly dependent upon the fulfillment of control goals. The cost of the modules, on the other hand, is subject to the components used to measure the state, and the hardware used for actuation. Therefore, obtaining a good control performance with cheap hardware is a challenge for control specific issues. In this paper, we describe an adaptive fuzzy sliding mode control scheme implemented on the control of 3-DOF I-Cubes links, which operate in a highly information-limited environment due to the size constraints, and which are bipartite. The tuning law is justified both in continuous time and in discrete time cases of sliding mode control approach. The implementation results justify the theoretical foundations and strongly recommend the approach due to its low computational cost together with the robustness against disturbances and uncertainties.
645-661

REFERENCES

References: 

[1] Paredis, C. J.-J. and Khosla P. K., “Kinematic Design of Serial Link Manipulators from Task Specifications,” Int. J. of Robotics Research, Vol.12, No.3, pp.274-287, 1993.
[2] Neville, B. and Sanderson, A., “Tetrabot Family Tree: Modular Synthesis of Kinematic Structures for Parallel Robotics,” Proc. IEEE / RSJ Int. Symposium of Robotics Research, pp.382-390, 1996.
[3] Fukuda, T. and Kawaguchi, Y., “Cellular Robotic System as One of the Realization of Self -Organizing Intelligent Universal Manipulator,” Proc. of the IEEE Int. Conf. on Robotics and Automation, pp.662-667, 1990.
[4] Pamecha, A., Chiang, C.-J., Stein, D. and Chirikjian, G. S., “Design and Implementation of Metamorphic Robots,” Proc. ASME Design Eng. Tech. Conf. and Comp. in Engineering Conf., Irvine CA, 1996.
[5] Yoshida, E., Murata, S., Tomita, K., Kurokawa, H. and Kokaji, S., “Experiments of Self-Repairing Modular Machine,” Distributed Autonomous Robotic Systems 3, H. Lueth, R. Dillmann, P. Dario, H. Wörn, (eds.), Springer-Verlag, pp.119-128, 1998.
[6] Vona, M. and Rus, D. L., “A Physical Implementation of the Self-reconfiguring Cristalline Robot,” Proc. of the IEEE Int. Conf. on Robotics and Automation, pp.1726-1733, 2000.
[7] Kotay, K. and Rus, D. L., “The Inchworm Robot: A Multi-Functional System,” Autono-mous Robots, Vol.8, No.1, pp.53-69, 2000.
[8] Yim, M., Duff, D. and Roufas, K. D., “PolyBot: A Modular Reconfirurable Robot,” Proc.IEEE Int. Conf. on Robotics and Automation, pp.514-520, 2000.
[9] Castano, A., Shen, W.-M. and Will, P., “CONRO: Towards Deployable Robots with Inter-Robots Metamorphic Capabilities,” Autonomous Robots, Vol.8, No.3, pp.309-324, 2000.
[10] Kotay, K. and Rus, D.L., “Motion Synthesis for the Self-Reconfiguring Robotic Molecule,” Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Vol.2, pp.843-851, 1998.
[11] Murata, S., Kurokawa, H., Yoshida, E., Tomita, K. and Kokaji, S., “A 3-D Self-Reconfigurable Structure,” Proc. IEEE Int. Conf. on Robotics and Automation, pp.432-439, 1998.
[12] Yoshida, E., Murata, S., Kaminura, A., Tomita, K., Korokawa, H. and Kokaji, S., “Motion Planning of Self - reconfigurable Modular Robot,” Proc. of the 7th Int. Symp. on Experimental Robotics, pp.375-384, 2000.
[13] Bojinov, H., Casal, A. and Hogg, T., “Emergent Structures in Modular Self-reconfigurable Robots,” Proc. IEEE Int. Conf. on Robotics and Automation, pp.1734-1742, 2000.
[14] Ünsal, C. and Khosla, P. K., “A Multi-Layered Planner for Self-Reconfiguration of a Uniform Group of I-Cube Modules,” Proc. 2001 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2001.
[15] Jang, J.-S. R., Sun, C.-T., and Mizutani, E., Neuro-Fuzzy and Soft Computing, PTR Prentice-Hall, 1997.
[16] Wang, L. X., A Course in Fuzzy Systems and Control, PTR Prentice-Hall, 1997.
[17] Hung, J. Y., Gao, W. and Hung, J. C., “Variable Structure Control: A Survey,” IEEE Trans. on Industrial Electronics, Vol. 40, No. 1, pp. 2-22, 1993.
[18] Young, K. D., Utkin, V. I. and Özguner, Ü., “A Control Engineer’s Guide to Sliding Mode Control,” IEEE Trans. on Control
660 Adaptive Fuzzy Sliding Mode Control For A Class Of Bipartite Modular Robotic Systems
Mehmet Önder EFE, Lemi Dağhan ACAY, Cem ÜNSAL, Pradeep K. KHOSLA
Systems Technology, Vol. 7, No. 3, pp. 328-342, 1999.
[19] Utkin, V. I., Sliding Modes in Control Optimi-zation, Springer Verlag, New York, 1992.
[20] Efe, M. Ö., “Variable Structure Systems Theory Based Training Strategies for Computationally Intelligent Systems,” Ph.D. Dissertation, Bogazici University, 2000.
[21] Sarpturk, S. Z., Istefanopulos, Y. and Kaynak, O., “On the Stability of Discrete-Time Sliding Mode Control Systems,” IEEE Trans. on Automatic Control, Vol. 32, No. 10, pp. 930-932, 1987.
[22] Gao, W., Wang, Y. and Homaifa, A., “Discrete-Time Variable Structure Control Systems”, IEEE Trans. on Industrial Electronics, Vol. 42, No. 2, pp. 117-122, 1995.
[23] Sira-Ramirez, H., “Non-linear Discrete Variable Structure Systems in Quasi-Sliding Mode,” Int. Journal of Control, Vol. 54, No. 5, pp. 1171-1187, 1991.
[24] Chen, X. and Fukuda, T., “Computer-Controlled Continuous-Time Variable Structure Systems with Sliding Modes,” Int. Journal of Control, Vol. 67, No. 4, pp. 619-639, 1997.
[25] Palm, R. and John, R., “Supervisory Fuzzy Control of an Exhaust Measuring System,” Proc. of the Fifth IEEE Int. Conf. on Fuzzy Systems, Vol. 1, pp. 479-485, 1996.
[26] Xu, H., Sun, F. and Sun, Z., “The Adaptive Sliding Mode Control based on a Fuzzy Neural Network for Manipulators,” IEEE Int. Conf. on Systems, Man and Cybernetics, Vol. 3, pp. 1942-1946, 1996.
[27] Fang, Y., Chow, T. W. S. and Li, X. D., “Use of a Recurrent Neural Network in Discrete Sliding-Mode Control,” IEEE Proc. Control Theory Appl., Vol. 146, No. 1, pp. 84-90, 1999.
[28] ozn~Mu, D. and Sbarbaro, D., “An Adaptive Sliding-Mode Controller for Discrete Nonlinear Systems,” IEEE Trans. on Industrial Electronics, Vol. 47, No. 3, pp. 574-581, 2000.
[29] Ünsal, C., Kiliççöte, H., Patton M. and Khosla, P. K., “Motion Planning for a Modular Self-reconfiguring Robotic System,” Distributed Autonomous Robotic Systems 4, Springer-Verlag, pp.165-175, 2000.
[30] Ünsal, C., Kılıççöte, H. and Khosla, P. K., “A Modular Self-Reconfigurable Bipartite Robotic System: Implementation and Motion Planning,” Autonomous Robots, v.10, no.1, pp. 23-40, 2001.
[31] Ünsal, C. and Khosla, P. K., “Solutions for 3-D Self-reconfiguration in a Modular Robotic System: Implementation and Motion Planning,” Proceedings of SPIE, Sensor Fusion and Decentralized Control in Robotic Systems III, November 2000.
[32] Yen, J. and Langari, R., Fuzzy Logic, PTR Prentice-Hall, New Jersey, 1999.
[33] Passino, K. M. and Yurkovich, S., Fuzzy Control, Addison-Wesley, California, 1998.
[34] Sira-Ramirez, H. and Colina-Morles, E., “A Sliding Mode Strategy for Adaptive Learning in Adalines,” IEEE Trans. on Circuits and Systems – I: Fundamental Theory and Applications, Vol.42, No.12, pp.1001-1012, 1995.
[35] Yu, X., Zhihong, M. and Rahman, S. M. M., “Adaptive Sliding Mode Approach for Learning in a Feedforward Neural Network,” Neural Computing and Applications, Vol.7, pp.289-294, 1998.

Thank you for copying data from http://www.arastirmax.com