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KURSAD GOKCE1,* , YILMAZ UYAROĞLU2
This paper investigates the stability and tracking performance of discrete-time chaotic systems in the presence of external disturbance and noise. For this purpose, a neural network control scheme is developed on the basis of a novel adaptive learning rate to stabilize the chaotic motion of discrete-time chaotic systems to a fixed point as well as to track the desired reference trajectory. The effectiveness of the proposed method is investigated through simulation studies on 2 dimensional Lozi map and performance comparison has been made with well-known backstepping control strategy..
Adaptive control, Learning systems, Lynapunov, Neural network, Chaos, Nonlinear systems.
KURSAD GOKCE, YILMAZ UYAROĞLU, Adaptive neural network based stabilization and trajectory tracking control of discrete-time chaotic systems, Optoelectronics and Advanced Materials - Rapid Communications, 9, 7-8, July-August 2015, pp.1022-1027 (2015).
Submitted at: April 22, 2015
Accepted at: June 24, 2015
Optoelectronics and Advanced Materials - Rapid Communications
(2023): 0.5 - 2023 Journal Citation Reports (Clarivate Analytics, 2024)
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