Adaptive Evolutionary Optimization Algorithms for Simple Fuzzy Controller Tuning Dedicated to Servo Systems - Fuzzy Modeling and Control: Theory and Applications - page 166

Precup, R.-E., David, R.-C., Petriu, E. M., Preitl, S., & Paul, A. S. (2011b). Gravitational search
algorithm-based tuning of fuzzy control systems with a reduced parametric sensitivity. Advances
in Intelligent and Soft Computing , 96 , 141-150. (Springer-Verlag).
Precup, R.-E., David, R.-C., Petriu, E. M., Preitl, S., & Radac, M.-B. (2011c). Gravitational search
algorithms in fuzzy control systems tuning. In Proceedings 18th world Congress of the interna-
tional federation of automatic control , pp. 13624-13629.
Precup, R.-E., David, R.-C., Petriu, E. M., Preitl, S., & Radac, M.-B. (2012a). Fuzzy control sys-
tems with reduced parametric sensitivity based on simulated annealing. IEEE Transactions on
Industrial Electronics , 59 , 3049-3061.
Precup, R.-E., David, R.-C., Petriu, E. M., Preitl, S., & Radac, M.-B. (2013a). Fuzzy logic-based
adaptive gravitational search algorithm for optimal tuning of fuzzy controlled servo systems. IET
Control Theory and Applications , 7 , 99-107.
Precup, R.-E., David, R.-C., Petriu, E. M., Radac, M.-B., Preitl, S., &Fodor, J. (2013b). Evolutionary
optimization-based tuning of low-cost fuzzy controllers for servo systems. Knowledge-Based
Systems , 38 , 74-84
Precup, R.-E., & Hellendoorn, H. (2011). A survey on industrial applications of fuzzy control.
Computers in Industry , 62 (3), 213-226.
Precup, R.-E., Radu-Codrut, D., Petriu, E. M., Preitl, S., & Radac, M.-B. (2012b). Novel adap-
tive gravitational search algorithm for fuzzy controlled servo systems. IEEE Transactions on
Industrial Informatics , 8 , 791-800.
Preitl, S., & Precup, R.-E. (1999). An extension of tuning relations after symmetrical optimum
method for PI and PID controllers. Automatica , 35 , 1731-1736.
Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm.
Information Sciences , 179 , 2232-2248.
Saeidi-Khabisi, F.-S., & Rashedi, E. (2012). Fuzzy gravitational search algorithm. In Proceedings
2nd international econference on computer and knowledge engineering , pp. 156-160.
Srivastava, P. R., Chis, M., Deb, S., & Yang, X.-S. (2012). An efficient optimization algorithm for
structural software testing. International Journal of Artificial Intelligence , 8 , 68-77.
Taleizadeh, A. A., Akhavan-Niaki, S.-T., Aryanezhad, M.-B., & Shafii, N. (2013). A hybrid method
of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with
stochastic replenishments and fuzzy demand. Informational Sciences , 220 , 425-441.
Teodorescu, H.-N. (2012). Taylor and bi-local piecewise approximations with neuro-fuzzy systems.
Study Infection Control , 21 , 367-376.
Tsakonas, A. (2013). Local and global optimization for Takagi-Sugeno fuzzy system by memetic
genetic programming. Expert Systems with Applications , 40 , 3282-3298.
Skrjanc, I., Blazic S., & Matko, D. (2002). Direct fuzzy model-reference adaptive control. Interna-
tional Journal of Intelligent Systems , 17 , 943-963
Valdez, F., Melin, P., & Castillo, O. (2011). An improved evolutionary method with fuzzy logic
for combining particle swarm optimization and genetic algorithms. Applied Soft Computing , 11 ,
2625-2632.
Va ˘scák, J. (2012). Adaptation of fuzzy cognitive maps by migration algorithms. Kybernetes , 41 ,
429-443.
Wu, C.-T., Tien, J.-P., & Li, T. S. (2012). Integration of DNA and real coded ga for the design
of PID-like fuzzy controllers. In Proceedings 2012 IEEE International Conference on Systems,
Man, and Cybernetics , (pp. 2809-2814).
Zahiri, S. (2012). Fuzzy gravitational search algorithm: An approach for data mining. Iranian
Journal of Fuzzy Systems , 9 , 21-37.