论文信息 - Evolutionary modeling of a process system

Evolutionary modeling of a process system

In this paper, a Genetic Algorithm (GA) modeling system is proposed. The GA is an evolutionary computational method that simulates the mechanisms of heredity or evolution of living things, and it is utilized in optimization and in searching for optimized solutions. Most process systems have nonlinearities, so it is necessary to anticipate exactly such systems. However, it is difficult to make a suitable model for nonlinear systems, because most nonlinear systems have a complex structure. Therefore the newly proposed method of modeling for nonlinear systems uses GA. Then according to the newly proposed scheme, the optimal structure and parameters of the nonlinear model are automatically generated.

Toru Yamamoto | Kazuo Kawada | Kayoko Hayashi

[1] Sheng Chen,et al. Representations of non-linear systems: the NARMAX model , 1989 .

[2] Kumpati S. Narendra,et al. Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[3] R. Boggia,et al. Genetic algorithms as a strategy for feature selection , 1992 .

[4] Hiroaki Aizawa,et al. Development of sensor materials for fluorescence thermometer application using LED excitation , 2009, 2009 ICCAS-SICE.

[5] Yoshiro Yamada,et al. Performance evaluation of WC-C peritectic high-temperature fixed point , 2009, 2009 ICCAS-SICE.

[6] Yasue Mitsukura,et al. A system identification method using a hybrid-type genetic algorithm , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

[7] Nobuo Fujii,et al. Application of Genetic Programming to System Modeling from Input-Output Data , 1998 .

[8] Toru Yamamoto,et al. A Design of Generalized Minimum Variance Controllers Using a GMDH Network for Nonlinear Systems , 2001 .

[9] Toru Yamamoto,et al. A Design of CMAC Based Intelligent PID Controllers , 2003, ICANN.

[10] Lang Zi-Qiang,et al. On identification of the controlled plants described by the Hammerstein system , 1994 .