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Identification of an Mechanism Systems by Using the Modified PSO Method

Authors: Chih-Cheng Kao, Hsin- Hua Chu


This paper mainly proposes an efficient modified particle swarm optimization (MPSO) method, to identify a slidercrank mechanism driven by a field-oriented PM synchronous motor. In system identification, we adopt the MPSO method to find parameters of the slider-crank mechanism. This new algorithm is added with “distance" term in the traditional PSO-s fitness function to avoid converging to a local optimum. It is found that the comparisons of numerical simulations and experimental results prove that the MPSO identification method for the slider-crank mechanism is feasible.

Keywords: Slider-crank mechanism, distance, systemidentification, modified particle swarm optimization.

Digital Object Identifier (DOI):

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[1] Viscomi, B. V., and Arye, R. S., "Nonlinear Dynamic Response of Elastic Slider-Crank Mechanism" ASME J. of Eng. for Industry, Vol. 93, pp. 251-262, 1971.
[2] Fung, R. F., "Dynamic Response of the Flexible Connecting Rod of a Slider-Crank Mechanism with Time-Dependent Boundary Effect" Computer & Structure, 63, No. 1,pp. 79-90, 1997.
[3] Fung, R. F., Lin, F. J., Huang, J. S. and Wang, Y. C., "Application of Sliding Mode Control with a Low-pass Filter to the Constantly Rotating Slider-Crank Mechanism" The Japan Society of Mechanical Engineers, C, 40, No. 4, pp 717-722, 1997.
[4] Lin, F. J., Fung, R. F., and Lin, Y. S., "Adaptive Control of Slider-Crank Mechanism Motion: Simulation and Experiments", International Journal of System Science, 28, No. 12, pp. 1227-1238, 1997.
[5] Kennedy, J., Eberhart, R. C., "Particle Swarm Optimization", Proceedings of the IEEE International Joint Conference on Neural Networks, IEEE Press, pp. 1942-1948, 1995.
[6] Eberhart, R. C., Kennedy, J., "A New Optimizer Using Particle Swarm Theory", Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan, pp.39-43, 1995.
[7] Wu, S. L. and Lin, S. K., 1997, "Implementation of damped-rate resolvedacceleration robot control," Control Engineering Practice, Vol. 5, No. 6, pp. 791-800.
[8] Campa, R., Kelly, R. and Garcia, E., 2001, "On stability of the resolved acceleration control," In Proc. 2001 IEEE Int. Conf. On Robotics and Automation, pp. 3523-3528.
[9] Kennedy, J., "The Particle Swarm: Social Adaptation of Knowledge", Proceedings of the IEEE International Conference on Evolutionary Computation, Indianapolis, USA, pp. 303-308, 1997.
[10] Naka, S., Genji, T., Yura, T., Fukuyama, Y., "A Hybrid Particle Swarm Optimization for Distribution State Estimation", IEEE Transactions on Power systems Vol. 18, No.1, pp.60-68, 2003.
[11]Shi, Y., Eberhart, R.C. ," Empirical Study of Particle Swarm Optimization ",Proceedings of the IEEE Congress on Evolutionary Computation, IEEE Press, pp.1945-1950, 1999.
[12] Lin, W. M., Cheng, F. S., and Tsay, M. T., "Nonconvex Economic Dispatch by Integrated Artificial Intelligence", IEEE Transactions on Power systems, Vol. 16, No. 2, pp. 307-311, 2001.
[13] Lin, W. M., Cheng, F. S., and Tsay, M. T., "An Improved Tabu Search for Economic Dispatch With Multiple Minima", IEEE Transactions on Power systems, Vol. 17, No. 1, pp. 108-112, 2002.
[14] Zhang, X., Huang, Y., Liu, J., Wang, X., and Gao, F., "A Method Identifying the Parameters of Bouc-Wen Hysteretic Nonlinear Model Based on Genetic Algorithm", Intelligent Processing Systems, pp. 602- 605, 1997.
[15] Ha, J. L., Kung, Y. S., Fung, R. F., and Hsien, S. C., "A Comparison of Fitness Functions for the Identification of Piezoelectric Hysteretic Actuator Based on the Real-Coded Genetic Algorithm", Sensors and Actuators , Vol.132, pp.643-650, 2006.