Ching-Chang Wong This email address is being protected from spambots. You need JavaScript enabled to view it.¹, Shih-An Li¹ and Hou-Yi Wang¹

¹Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.

REFERENCES

1. [1] Chent, S., Istepaniant, R. H., Whidbornet, J. F. and Wu, J., “Adaptive Simulated Annealing for Designing Finite-Precision PID Controller Structures,” IEE Colloquium on Optimisation in Control: Methods and Applications, pp. 1
   3 (1998).
2. [2] Kwok, D. P. and Sheng, F., “Genetic Algorithm and Simulated Annealing for Optimal Robot Arm PID Control,” IEEE Conference on Evolutionary Computation, pp. 707
   712 (1994).
3. [3] Mitsukura, Y., Yamamoto, T. and Kaneda, M., “A Genetic Tuning Algorithm of PID Parameters,” Inference on Systems, Man, and Cybernetics, Vol. 1, pp. 923
   928 (1997).
4. [4] Krohling, R. A., Jaschek, H. and Rey, J. P., “Designing PI/PID Controller for a Motion Control System Based on Genetic Algorithm,” 12th IEEE International Symposium on Intelligent Control,July, pp. 125
   130 (1997).
5. [5] Davis, L., Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York (1991).
6. [6] Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Mass (1989).
7. [7] Wong, C. C. and Chen, C. C., “A GA-Based Method for Constructing Fuzzy Systems Directly from Numerical Data,” IEEE Transactions on Systems, Man and Cybernetics, Vol. 30, pp. 904
   911 (2000).
8. [8] Wong, C.,C., Lin, B. C. and Chen, C. C., “Fuzzy System Design by a GA-Based Method for Data Classification,” Cybernetics and Systems: An International Journal, Vol. 33, pp. 253
   270 (2002).
9. [9] Wong, C. C., Lin, B. C., Lee, S. A. and Tsai, C. H., “GA-Based Fuzzy System Design in FPGA for an Omni-Directional Mobile Robot,” Journal of Intelligent & Robotic Systems, Vol. 44, pp. 327
   347 (2005).
10. [10] Kennedy, J. and Eberhart, R., “Particle Swarm Optimization,” IEEE International Conference on Neural Networks, pp. 1942
    1948 (1995).
11. [11] Shi, Y. and Eberhart, R., “A Modified Particle Swarm Optimizer,” IEEE Congress on Evolutionary Computation, May, pp. 69
    73 (1998).
12. [12] Angeline, P. J., “Using Selection to Improve Particle Swarm Optimization,” IEEE Congress on Evolutionary Computation, May, pp. 84
    89 (1998).
13. [13] Shi, Y. and Eberhart, R. C., “Empirical Study of Particle Swarm Optimization,” IEEE Congress on Evolutionary Computation, July, pp. 1945
    1950 (1999).
14. [14] Clerc, M. and Kennedy, J., “The Particle Swarm
    Explosion, Stability, and Convergence in a Multidimensional Complex Space,” IEEE Transactions on Evolutionary Computation, Vol. 6, pp. 58
    73 (2002).
15. [15] Parsopoulous, K. E. and Vrahatis, M. N., ”On the Computation of All Global Minimizers through Particle Swarm Optimization,” IEEE Transactions on Evolutionary Computation, Vol. 8, pp. 211
    224 (2004).
16. [16] Yoshida, H., Kawata, K., Fukuyama, Y. and Nakanishi, Y., “A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment,” IEEE Transactions on Power Systems, Vol. 15, pp. 1232
    1239 (2000).
17. [17] Gaing, Z. L., “A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System,” IEEE Transactions on Energy Conversion, Vol. 19, pp. 384
    394 (2004).
18. [18] Liu, Y., Zhang, J. and Wang, S., “Optimization Design Based on PSO Algorithm for PID Controller,” 5th World Congress on Intelligent Control and Automation, Vol. 3, pp. 2419
    2422 (2004).
19. [19] Eberhart, R. C. and Shi, Y., “Comparison between Genetic Algorithms and Particle Swarm Optimization,” IEEE Congress on Evolutionary Computation, May, pp. 611
    616 (1998).
20. [20] Shi, X. H., Liang, Y. C., Lee, H. P., Lu, C. and Wang, L. M., “An Improved GA and a Novel PSO-GA-Based Hybrid Algorithm,” Information Processing Letters, Vol. 93, pp. 255
    261 (2005).
21. [21] Kawabe, T. and Tagami, T., “A Real Coded Genetic Algorithm for Matrix Inequality Design Approach of Robust PID Controller with Two Degrees of Freedom,” 12th IEEE International Symposium on Intelligent Control, July, pp. 119
    124 (1997).
22. [22] Su, M. C. and Chang, H. T., “A Real-Valued GABased Approach to Extracting Fuzzy Rules for System Identification,” International Joint Conference of CFSA/IFIS/SOFT’ 95 on Fuzzy Theory and Applications, pp. 41
    46 (1995).