Chaotification of Discrete Dynamical Systems Governed by Continuous Maps and Evolved Fuzzy NN Control

Fuzzy Optimization and Modeling Journal

دوره 2، شماره 1، فروردین 2021، صفحه 37-41   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.30495/fomj.2021.681566

نویسنده

Tim Chen, YC Huang, J CY Chen^*

Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

چکیده

The truth of the false extraction method of digital control system is developed in the false reality to overcome the challenge and continue to design controllers for real systems. However, the scheme to control the false extraction of real system is complex, so it is not suitable for use in practice. In order to verify the asymptotic state with a false reality can be considered by discrete systems, this article calculates a neural neural network (NN) controller with a mean bat algorithm. This view of this evolved fuzzy NN control is performed using the domain of false reality can be considered from model to model transformation polylinear linear rule of thumb, and the new measures on asymptotic stability. Simulation results show that the proposed method can make the system asymptotically stable in discrete time. The dual model of strength and EBA also provides flexibility and efficiency in finding solutions for managed systems.

کلیدواژه‌ها

Evolved control؛ Nonlinear systems؛ Neural network