×

Optimization of interval type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms. (English) Zbl 1167.93385

Summary: We describe a tracking controller for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on type-2 fuzzy logic theory and genetic algorithms. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems.

MSC:

93C85 Automated systems (robots, etc.) in control theory
93C42 Fuzzy control/observation systems
93C73 Perturbations in control/observation systems
90C59 Approximation methods and heuristics in mathematical programming
PDF BibTeX XML Cite
Full Text: DOI

References:

[1] Alcalá, R.; Alcalá-Fdez, J.; Herrera, F., A proposal for the genetic lateral tuning of linguistic fuzzy systems and its interaction with rule selection, IEEE transactions on fuzzy systems, 15, 4, 616-635, (2007) · Zbl 1147.68063
[2] Alcalá, R.; Gacto, M.J.; Herrera, F.; Alcalá-Fdez, J., A multi-objective genetic algorithm for tuning and rule selection to obtain accurate and compact linguistic fuzzy rule-based systems, International journal of uncertainty, fuzziness and knowledge-based systems, 15, 5, 539-557, (2007) · Zbl 1147.68063
[3] L. Astudillo, O. Castillo, L. Aguilar, Intelligent control of an autonomous mobile robot using type-2 fuzzy logic, in: Proceedings of ICAI’06, 2006, pp. 565-570.
[4] S. Bentalba, A. El Hajjaji, A. Rachid, Fuzzy control of a mobile robot: a new approach, in: Proceedings of the IEEE International Conference on Control Applications, Hartford, CT, October 1997, pp. 69-72.
[5] Bloch, A.M., Nonholonomic mechanics and control, (2003), Springer Verlag New York · Zbl 1045.70001
[6] Brockett, R.W., Asymptotic stability and feedback stabilization, (), 181-191 · Zbl 0528.93051
[7] Casillas, J.; Cordon, O.; del Jesús, M.J.; Herrera, F., Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction, IEEE transaction on fuzzy systems, 13, 1, 13-29, (2005)
[8] Castillo, O.; Melin, P., Soft computing for control of non-linear dynamical systems, (2001), Springer-Verlag Heidelberg, Germany · Zbl 0992.93500
[9] Chi, Z.; Yan, H.; Pham, T., Fuzzy algorithms: with applications to image processing and pattern recognition, (1996), World Scientific Singapore · Zbl 0942.68001
[10] Chwa, D., Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates, IEEE transactions on control systems technology, 12, 4, 633-644, (2004)
[11] Cordon, O.; Gomide, F.; Herrera, F.; Hoffmann, F.; Magdalena, L., Ten years of genetic fuzzy systems: current framework and new trends, Fuzzy sets and systems, 141, 1, 5-31, (2004) · Zbl 1050.93513
[12] DeJong, K., Learning with genetic algorithms: an overview, Machine learning, 3, 3, 121-138, (1988)
[13] Driankov, D.; Hellendoorn, H.; Reinfrank, M., An introduction to fuzzy control, (1993), Springer Berlin
[14] Duc Do, K.; Zhong-Ping, J.; Pan, J., A global output-feedback controller for simultaneous tracking and stabilizations of unicycle-type mobile robots, IEEE transactions on automatic control, 30, 589-594, (2004)
[15] Fierro, R.; Lewis, F.L., Control of a nonholonomic mobile robot using neural networks, IEEE transactions on neural networks, 9, 4, 589-600, (1998)
[16] Fukao, T.; Nakagawa, H.; Adachi, N., Adaptive tracking control of a nonholonomic mobile robot, IEEE transactions on robotics and automation, 16, 5, 609-615, (2000)
[17] Goldberg, D.E., Genetic algorithms in search, and machine learning, (1989), Addison-Wesley Reading, MA · Zbl 0721.68056
[18] Goldberg, D.E., The design of competent genetic algorithms: steps toward a computational theory of innovation, (2002), Kluwer Academic Publishers Dordrecht
[19] Hagras, H.A., A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots, IEEE transactions on fuzzy systems, 12, 4, 524-539, (2004)
[20] Holland, J.H., Adaptation in natural and artificial systems, (1975), University of Michigan Press Ann Arbor
[21] S. Ishikawa, A method of indoor mobile robot navigation by fuzzy control, in: Proc. Int. Conf. Intell. Robot. Syst., Osaka, Japan, 1991, pp. 1013-1018.
[22] Karnik, N.N.; Mendel, J., Centroid of a type-2 fuzzy set, Information sciences, 132, 1-4, 195-220, (2001) · Zbl 0982.03030
[23] Khalil, H., Nonlinear systems, (2002), Prentice Hall New York
[24] Kristic, M.; Kanellakopoulos, I.; Kokotovic, P., Nonlinear and adaptive control design, (1995), Wiley-Interscience
[25] Lee, T.H.; Leung, F.H.F.; Tam, P.K.S., Position control for wheeled mobile robot using a fuzzy controller, Ieee, 525-528, (1999)
[26] Lee, T.-C.; Song, K.-T.; Lee, C.-H.; Teng, C.-C., Tracking control of unicycle-modeled mobile robot using a saturation feedback controller, IEEE transactions on control systems technology, 9, 305-318, (2001)
[27] Liang, Q.; Mendel, J.M., Interval type-2 fuzzy logic systems: theory and design, IEEE transactions on fuzzy systems, 8, 5, 535-550, (2000)
[28] D. Liberzon, Switching in Systems and Control, Bikhauser, 2003. · Zbl 1036.93001
[29] Man, K.F.; Tang, K.S.; Kwong, S., Genetic algorithms, concepts and designs, (2000), Springer, pp. 5-10
[30] Mendel, J.; Mouzouris, George C., Type-2 fuzzy logic systems, IEEE transactions on fuzzy systems, 7, December, 643-658, (1999)
[31] Mendel, J.; John, R., Type-2 fuzzy sets made simple, IEEE transactions on fuzzy systems, 10, April, 117-127, (2002)
[32] Mendel, J.; Bob John, Robert I., Type-2 fuzzy sets made simple, IEEE transactions on fuzzy systems, 10, 2, (2002)
[33] Mendel, J., Uncertain rule-based fuzzy logic systems, (2001), Prentice Hall · Zbl 0978.03019
[34] Mendel, J., On a 50
[35] ()
[36] W. Nelson, I. Cox, Local path control for an autonomous vehicle, in: Proceedings of the IEEE Conference on Robotics and Automation, 1988, pp. 1504-1510
[37] Paden, B.; Panja, R., Globally asymptotically stable PD+ controller for robot manipulator, International journal of control, 47, 6, 1697-1712, (1988) · Zbl 0649.93052
[38] Passino, K.M.; Yurkovich, S., Fuzzy control, (1998), Addison Wesley Longman USA
[39] S. Pawlowski, P. Dutkiewicz, K. Kozlowski, W. Wroblewski, Fuzzy logic implementation in mobile robot control, in: Second Workshop on Robot Motion and Control, October 2001, pp. 65-70.
[40] ()
[41] R. Sepulveda, O. Castillo, P. Melin, O. Montiel, An efficient computational method to implement type-2 fuzzy logic in control applications, in: Analysis and Design of Intelligent Systems using Soft Computing Techniques, Advances in Soft Computing, vol. 41, June 2007, pp. 45-52
[42] Sepúlveda, R.; Castillo, O.; Melin, P.; Rodríguez-Díaz, A.; Montiel, O., Experimental study of intelligent controllers under uncertainty using type-1, and type-2 fuzzy logic, Information sciences, informatics and computer science intelligent systems applications, 177, 10, 2023-2048, (2007)
[43] Song, K.T.; Sheen, L.H., Heuristic fuzzy-neural network and its application to reactive navigation of a mobile robot, Fuzzy sets systems, 110, 3, 331-340, (2000)
[44] Takagi, T.; Sugeno, M., Fuzzy identification of systems and its application to modeling and control, IEEE transactions on systems, man, and cybernetics, 15, 1, (1985)
[45] C.-C. Tsai, H.-H. Lin, C.-C. Lin, Trajectory tracking control of a laser-guided wheeled mobile robot, in: Proceedings of the IEEE International Conference on Control Applications, Taipei, Taiwan, September 2004, pp. 1055-1059.
[46] Ulyanov, S.V.; Watanabe, S.; Yamafuji, K.; Litvintseva, L.V.; Rizzotto, G.G., Soft computing for the intelligent robust control of a robotic unicycle with a new physical measure for mechanical controllability, Soft computing, vol. 2, (1998), Springer-Verlag, pp. 73-88
[47] Zadeh, L.A., Outline of a new approach to the analysis of complex systems and decision processes, IEEE transactions on systems, man, and cybernetics, 3, 1, 28-44, (1973) · Zbl 0273.93002
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.