Guaranteed Cost Control Design of 4D Lorenz-Stenflo Chaotic System via T-S Fuzzy Approach

This paper investigates the guaranteed cost control of chaos problem in 4D Lorenz-Stenflo (LS) system via Takagi-Sugeno (T-S) fuzzy method approach. Based on Lyapunov stability theory and linear matrix inequality (LMI) technique, a state feedback controller is proposed to stabilize the 4D Lorenz-Stenflo chaotic system. An illustrative example is provided to verify the validity of the results developed in this paper

Synchronization of lai-chen (2016) chaotic system with active control

Most of the events in the real world show non-linear behavior. Such events are usually chaotic. Chaotic systems are highly sensitive to the initial conditions and parameters values, exhibit non-periodic properties, and some have a very broad frequency spectrum. Because of these features, chaotic systems are used in different branches of science such as encryption, communication, random number generators, prediction algorithms, computer games, biology, medicine. In this regard, a variety of chaotic and hyper-chaotic systems are introduced in the literature. However, because of chaotic systems are very sensitive to initial conditions and parameters, chaotic systems need to be synchronized in order to be used in chaos-based communication and encryption applications. In this study, a new chaotic system presented by Lai and Chen in 2016 was synchronized with active control method. Consequently, it is shown that the Lai-Chen chaotic system can be synchronized and used in chaos-based communication and encryption applications

Adaptive Second-Order Sliding Mode Algorithm-Based Modified Function Projective Synchronization of Uncertain Hyperchaotic Systems

This article proposes a synchronization technique for uncertain hyperchaotic systems in the modified function projective manner using integral fast terminal sliding mode (I-FTSM) and adaptive second-order sliding mode algorithm. The new I-FTSM manifolds are introduced with the aim of having the fast convergence speed. The proposed continuous controller not only results in the robustness and high-accuracy synchronization in the presence of unknown external disturbances and/or model uncertainties but also helps alleviating the chattering effect significantly. Numerical simulation results are provided to illustrate the effectiveness of the proposed control design technique and verify the theoretical analysis

Kaotik sistemlerin klasik ve zeki yaklaşımlar ile kontrolü

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Elektronik devreler için kaos istenmeyen bir davranıştır. Bu tezde, kaotik sistemlerin kontrolü için iyi bilinen bazı kaos kontrol yöntemleri ile yapay zekâ tekniklerinin birlikte kullanımı önerilmiştir. Chua devresinin kontrolü kayma kipli kontrol yöntemi, yapay sinir ağları ve ikisinin bir arada kullanımı ile, Bonhoeffer–van der Pol devresinin kontrolü pasif kontrol yöntemi, bulanık mantık ve ikisinin bir arada kullanımı ile, Colpitts devresinin kontrolü ise geri-beslemeli kontrol yöntemi, sinirsel-bulanık ağlar ve ikisinin bir arada kullanımı ile gerçekleştirilmiştir. Sonuçlar karşılaştırmalı grafikler ile sunulmuştur. Sonuçlar, önerilen yaklaşımın kaotik sistemlerin denge noktasına kontrolünü daha hızlı sağladığını göstermiştir.Chaos is an undesired behaviour for electronic circuits. In this thesis, usage of some well-known chaos control methods with artificial intelligence techniques is proposed for the control of chaotic systems. Sliding mode control method, artificial neural networks and using both of them are applied for the control of Chua's circuit, the passive control method, fuzzy logic and using both of them are applied for the control of Bonhoeffer–van der Pol circuit, and the feedback control method, adaptive neuro-fuzzy inference system and using both of them are applied for the control of Colpitts circuit. The results are presented by comparative figures. They show that the proposed approach provides the control of chaotic systems to their equilibrium points more effectively