Browsing by Author "Li, Shih-Yu"

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Adaptive synchronization of chaotic systems with unknown parameters via new backstepping strategy
(2012-11-01)
Li, Shih-Yu
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Yang, Cheng-Hsiung
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Lin, Chin-Teng
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Ko, Li-Wei
;
Chiu, Tien-Ting
In this paper, a new effective approach-backstepping with Ge-Yao-Chen (GYC) partial region stability theory (called BGYC in this article) is proposed to applied to adaptive synchronization. Backstepping design is a recursive procedure that combines the choice of a Lyapunov function with the design of a controller, and it presents a systematic procedure for selecting a proper controller in chaos synchronization. We further combine the systematic backstepping design and GYC partial region stability theory in this article, Lyapunov function can be chosen as a simple linear homogeneous function of states, and the controllers and the update laws of parameters shall be much simpler. Further, it also introduces less simulation error-the numerical simulation results show that the states errors and parametric errors approach to zero much more exactly and efficiently, which are compared with the original one. Two cases are presented in the simulation results to show the effectiveness and feasibility of our new strategy.
Chaos control of new Ikeda-Lorenz systems by GYC partial region stability theory
(2009-08-01)
Ge, Zheng-Ming
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Ho, Chun-Yen
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Li, Shih-Yu
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Chang, Ching-Ming
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機械工程學系
A new strategy to achieve chaos control by GYC partial region stability theory is proposed. By using the GYC partial region stability theory, the Lyapunov function is a simple linear homogeneous function of error states, the controllers are more simple and have less simulation error because they are in lower degree than that of traditional controllers. Simulation results for a new Ikeda-Lorenz system show the effectiveness of this strategy. Copyright (C) 2008 John Wiley & Sons, Ltd.
Chaos control of new Mathieu-van der Pol systems by fuzzy logic constant controllers
(2011-12-01)
Li, Shih-Yu
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機械工程學系
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Department of Mechanical Engineering
In this paper, a new fuzzy logic controller-fuzzy logic constant controller (FLCC) is introduced to chaotic signals controlling. The main ideas of the FLCC are described as follows: (1) proving the two chaotic systems are going to achieve asymptotically stable via Lyapunov direct method; (2) via detecting the sign of the errors, the appropriate fuzzy logic control scheme is operated; (3) choosing the upper bound and the lower bound of the error derivatives of the chaotic signals to be the consequent parts (corresponding controllers). Due to controllers in traditional method - derived by Lyapunov direct method, are always complicated, nonlinear form or the functions of errors, a new simplest controller-FLCC is presented in this paper to synchronize two chaotic signals. Through the FLCC, there are three main contributions can be obtained: (1) the mathematical models of the nonlinear chaotic systems can be unknown, all we have to do is capturing the signals of the unknown systems; (2) through the fuzzy logic rules, the strength of controllers can be adjusted via the corresponding membership functions (which are decided by the values of error derivatives); (3) by the FLCC, the chaotic system can be much more exactly and efficiently controlled to the trajectory of our goal than traditional ones. Three cases, original point, regular function and chaotic Qi system (with large values of initial conditions), are given to illustrate the effectiveness of our new FLC. (C) 2011 Elsevier B.V. All rights reserved.
Chaos control of new Mathieu-Van der Pol systems with new Mathieu-Duffing systems as functional system by GYC partial region stability theory
(2009-11-01)
Ge, Zheng-Ming
;
Li, Shih-Yu
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機械工程學系
;
Department of Mechanical Engineering
In this paper, a new strategy by using GYC partial region stability theory is proposed to achieve chaos control. Using the GYC partial region stability theory, the new Lyapunov function used is a simple linear homogeneous function of error states and the lower order controllers are much more simple and introduce less simulation error. Numerical simulations are given for new Mathieu-Van der Pol system and new Mathieu-Duffing system to show the effectiveness of this strategy. (C) 2009 Elsevier Ltd. All rights reserved.
Chaos generalized synchronization of an inertial tachometer with new Mathieu-Van der Pol systems as functional system by GYC partial region stability theory
(2012-03-01)
Yang, Cheng-Hsiung
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Chen, Tsung-Wen
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Li, Shih-Yu
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Chang, Ching-Ming
;
Ge, Zheng-Ming
A new strategy to achieve generalized chaos synchronization by GYC partial region stability theory is proposed. By using the GYC partial region stability theory the Lyapunov function is a simple linear homogeneous function of error states and the controllers are more simple and introduce less simulation error because they are in lower order than that of traditional controllers. In simulation examples, an inertial tachometer system and Mathieu-Van der Pol system are used. (C) 2011 Elsevier B.V. All rights reserved.
Chaos generalized synchronization of new Mathieu-Van der Pol systems with new Duffing-Van der Pol systems as functional system by GYC partial region stability theory
(2011-11-01)
Ge, Zheng-Ming
;
Li, Shih-Yu
;
機械工程學系
;
Department of Mechanical Engineering
In this paper, a new strategy by using GYC partial region stability theory is proposed to achieve generalized chaos synchronization. via using the GYC partial region stability theory, the new Lyapunov function used is a simple linear homogeneous function of states and the lower order controllers are much more simple and introduce less simulation error. Numerical simulations are given for new Mathieu-Van der Pol system and new Duffing-Van der Pol system to show the effectiveness of this strategy. (C) 2011 Elsevier Inc. All rights reserved.
Chaos synchronization and chaos control of quantum-CNN chaotic system by variable structure control and impulse control
(2010-06-01)
Yang, Cheng-Hsiung
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Ge, Zheng-Ming
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Chang, Ching-Ming
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Li, Shih-Yu
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機械工程學系
In this paper, we derive some less stringent conditions for the exponential and asymptotic stability of impulsive control systems with impulses at fixed times These conditions are then used to design an impulsive control law for the Quantum Cellular Neural Network chaotic system, which drives the chaotic state to zero equilibrium and synchronizes two chaotic systems. An active sliding mode control method is synchronizing two chaotic systems and controlling chaotic state to periodic motion state And a sufficient condition is drawn for the robust stability of the error dynamics, and is applied to guiding the design of the controllers. Finally, numerical results are used to show the robustness and effectiveness of the proposed control strategy. (C) 2010 Published by Elsevier Ltd
Chaos synchronization of double Duffing systems with parameters excited by a chaotic signal
(2008-11-11)
Ge, Zheng-Ming
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Li, Chien-Hao
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Li, Shih-Yu
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Chang, Ching Ming
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機械工程學系
Chaos synchronization by driving parameter for two uncoupled identical chaotic double Duffing systems is presented. Replacing two corresponding parameters of the identical systems by the same function of chaotic state variables of a third chaotic system, the synchronization or anti-synchronization of two uncoupled systems can be obtained. Numerical simulations are illustrated for either synchronization or anti-synchronization of which the occurrence depends significantly on initial conditions and on driving strength. Alternative complete synchronization and anti-synchronization is also discovered. (c) 2008 Published by Elsevier Ltd.
Chaotic Motions in the Real Fuzzy Electronic Circuits
(2013)
Li, Shih-Yu
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Yang, Cheng-Hsiung
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Lin, Chin-Teng
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Ko, Li-Wei
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Chiu, Tien-Ting
Fuzzy electronic circuit (FEC) is firstly introduced, which is implementing Takagi-Sugeno (T-S) fuzzy chaotic systems on electronic circuit. In the research field of secure communications, the original source should be blended with other complex signals. Chaotic signals are one of the good sources to be applied to encrypt high confidential signals, because of its high complexity, sensitiveness of initial conditions, and unpredictability. Consequently, generating chaotic signals on electronic circuit to produce real electrical signals applied to secure communications is an exceedingly important issue. However, nonlinear systems are always composed of many complex equations and are hard to realize on electronic circuits. Takagi-Sugeno (T-S) fuzzy model is a powerful tool, which is described by fuzzy IF-THEN rules to express the local dynamics of each fuzzy rule by a linear system model. Accordingly, in this paper, we produce the chaotic signals via electronic circuits through T-S fuzzy model and the numerical simulation results provided by MATLAB are also proposed for comparison. T-S fuzzy chaotic Lorenz and Chen-Lee systems are used for examples and are given to demonstrate the effectiveness of the proposed electronic circuit.
Fuzzy adaptive synchronization of time-reversed chaotic systems via a new adaptive control strategy
(2013-02-10)
Li, Shih-Yu
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Yang, Cheng-Hsiung
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Chen, Shi-An
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Ko, Li-Wei
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Lin, Chin-Teng
A novel adaptive control strategy is proposed herein to increase the efficiency of adaptive control by combining Takagi-Sugeno (T-S) fuzzy modeling and the Ge-Yao-Chen (GYC) partial region stability theory. This approach provides two major contributions: (1) increased synchronization efficiency, especially for parameters tracing and (2) a simpler controller design. Two simulated cases are presented for comparison: Case 1 utilizes normal adaptive synchronization, whereas Case 2 utilizes the Takagi-Sugeno (T-S) fuzzy model-based Lorenz systems to realize adaptive synchronization via the new adaptive scheme. The simulation results demonstrate the effectiveness and feasibility of our new adaptive strategy. (C) 2012 Elsevier Inc. All rights reserved.
Fuzzy Modeling and Synchronization of Chaotic Quantum Cellular Neural Networks Nano System via a Novel Fuzzy Model and Its Implementation on Electronic Circuits
(2010-11-01)
Ge, Zheng-Ming
;
Li, Shih-Yu
;
機械工程學系
;
Department of Mechanical Engineering
In this paper, a new fuzzy model is presented to simulate Quantum cellular neural networks nano system (called Quantum-CNN system). Through the new fuzzy model, the Quantum-CNN system is linearized to a simple form-linear coupling of two linear subsystems. Quantum-CNN system is a complicated nonlinear system. There are too more nonlinear terms in its dynamic equations, such as radical terms, square terms, sin and cos terms, etc. If the traditional T-S fuzzy model is used here, there would be 16 fuzzy rules and even 64 linear equations for modeling such a complex system. It is definitely an inefficient work. As a result, by using the new fuzzy model, the numbers of fuzzy rules can be reduced from 2(N) to 2 x N (where N is the number of nonlinear terms) and only two subsystems exist. Moreover, the LMI-based fuzzy synchronization of two fuzzy chaotic Q-CNN systems and its related theorem is proposed as well. Via using the new fuzzy model, only two feedback gains are needed in the fuzzy controllers. Finally, via using Taylor's expansion, the complicated nonlinear terms can be expanded to series form, and then the simplified Q-CNN system can be implemented on electronic circuits for secure communication. Simulation results in MATLAB and implementation of electronic circuits are given to show the effectiveness and feasibility of the new fuzzy model and the new approaches.
Fuzzy Modeling and Synchronization of Chaotic Quantum Cellular Neural Networks Nano System via a Novel Fuzzy Model and Its Implementation on Electronic Circuits
(2010-11-01)
Ge, Zheng-Ming
;
Li, Shih-Yu
;
機械工程學系
;
Department of Mechanical Engineering
In this paper, a new fuzzy model is presented to simulate Quantum cellular neural networks nano system (called Quantum-CNN system). Through the new fuzzy model, the Quantum-CNN system is linearized to a simple form-linear coupling of two linear subsystems. Quantum-CNN system is a complicated nonlinear system. There are too more nonlinear terms in its dynamic equations, such as radical terms, square terms, sin and cos terms, etc. If the traditional T-S fuzzy model is used here, there would be 16 fuzzy rules and even 64 linear equations for modeling such a complex system. It is definitely an inefficient work. As a result, by using the new fuzzy model, the numbers of fuzzy rules can be reduced from 2(N) to 2 x N (where N is the number of nonlinear terms) and only two subsystems exist. Moreover, the LMI-based fuzzy synchronization of two fuzzy chaotic Q-CNN systems and its related theorem is proposed as well. Via using the new fuzzy model, only two feedback gains are needed in the fuzzy controllers. Finally, via using Taylor's expansion, the complicated nonlinear terms can be expanded to series form, and then the simplified Q-CNN system can be implemented on electronic circuits for secure communication. Simulation results in MATLAB and implementation of electronic circuits are given to show the effectiveness and feasibility of the new fuzzy model and the new approaches.
Fuzzy Modeling and Synchronization of Two Totally Different Chaotic Systems via Novel Fuzzy Model
(2011-08-01)
Li, Shih-Yu
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Ge, Zheng-Ming
;
機械工程學系
;
Department of Mechanical Engineering
In this paper, a new fuzzy model is presented to simulate and synchronize two totally different and complicated chaotic systems, namely, 1) quantum cellular neural networks nanosystem (Quantum-CNN system) and 2) Qi system. Through the new fuzzy model, the following three main advantages can be obtained: 1) only two linear subsystems are needed; 2) the numbers of fuzzy rules can be reduced from 2(N) to 2 x N (comparing with the Takagi-Sugeno fuzzy model), where N is the number of nonlinear terms; 3) fuzzy synchronization of two different chaotic systems with different numbers of nonlinear terms can be achieved with only two sets of gain K. There are two examples in numerical simulation results to show the effectiveness and feasibility of our new model.
Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors
(2012-01-28)
Liao, Lun-De
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Chen, Chi-Yu
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Wang, I-Jan
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Chen, Sheng-Fu
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Li, Shih-Yu
A brain-computer interface (BCI) is a communication system that can help users interact with the outside environment by translating brain signals into machine commands. The use of electroencephalographic (EEG) signals has become the most common approach for a BCI because of their usability and strong reliability. Many EEG-based BCI devices have been developed with traditional wet- or micro-electro-mechanical-system (MEMS)-type EEG sensors. However, those traditional sensors have uncomfortable disadvantage and require conductive gel and skin preparation on the part of the user. Therefore, acquiring the EEG signals in a comfortable and convenient manner is an important factor that should be incorporated into a novel BCI device. In the present study, a wearable, wireless and portable EEG-based BCI device with dry foam-based EEG sensors was developed and was demonstrated using a gaming control application. The dry EEG sensors operated without conductive gel; however, they were able to provide good conductivity and were able to acquire EEG signals effectively by adapting to irregular skin surfaces and by maintaining proper skin-sensor impedance on the forehead site. We have also demonstrated a real-time cognitive stage detection application of gaming control using the proposed portable device. The results of the present study indicate that using this portable EEG-based BCI device to conveniently and effectively control the outside world provides an approach for researching rehabilitation engineering.
Generalized synchronization of chaotic systems with different orders by fuzzy logic constant controller
(2011-03-01)
Li, Shih-Yu
;
Ge, Zheng-Ming
;
機械工程學系
;
Department of Mechanical Engineering
The fuzzy logic constant controller (FLCC) is introduced in this paper. Unlike traditional method, a simplest controller is proposed via fuzzy logic design and Lyapunov direct method. Controllers in traditional method by Lyapunov direct method are always complicated or the functions of errors. We propose a new idea to design constant numbers as controllers, while the constant numbers are decided by the upper bound and the lower bound of the error derivatives. Via fuzzy logic rules, the strength of controllers in our new approach can be adjusted according to the error derivatives. Consequently, the slave system becomes exactly and efficiently synchronized to the trajectory of master system through FLCC. Two examples, Lorenz system and four order Chen-Lee system, are presented to illustrate the effectiveness of the new controllers in chaos generalized synchronization. (C) 2010 Elsevier Ltd. All rights reserved.
Generalized synchronization of chaotic systems with different orders by fuzzy logic constant controller (vol 38, pg 2302, 2011)
(2012-02-15)
Li, Shih-Yu
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Ge, Zheng-Ming
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機械工程學系
;
Department of Mechanical Engineering
Generalized synchronization of chaotic systems with different orders by fuzzy logic constant controller (vol 38, pg 2302, 2011)
(2011-02-15)
Li, Shih-Yu
;
Ge, Zheng-Ming
;
機械工程學系
;
Department of Mechanical Engineering
Generating tri-chaos attractors with three positive Lyapunov exponents in new four order system via linear coupling
(2012-08-01)
Li, Shih-Yu
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Huang, Sheng-Chieh
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Yang, Cheng-Hsiung
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Ge, Zheng-Ming
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機械工程學系
This paper presents a new hyperchaotic system with three positive Lyapunov exponents (called Tri-Chaos). Via linear coupling, Mathieu, and van der Pol systems are coupled with each other and then become a new four order system-Mathieu-van der Pol autonomous system. As we know, two positive Lyapunov exponents confirm hyperchaotic nature of its dynamics and it means that the system can present more complicated behavior than ordinary chaos. We further generate three positive Lyapunov exponents in a new coupled nonlinear system and anticipate the advanced application in secure communication. Not only a new chaotic system with three Lyapunov exponents is proposed, but also its implementation of an electronic circuit is put into practice in this article. The phase portrait, electronic circuit, power spectrum, Lyapunov exponents, and 2-D and 3-D parameter diagram of tri-chaos with three positive Lyapunov exponents of the new system will be shown in this paper.
Implementation on Electronic Circuits and RTR Pragmatical Adaptive Synchronization: Time-Reversed Uncertain Dynamical Systems' Analysis and Applications
(2013)
Li, Shih-Yu
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Yang, Cheng-Hsiung
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Ko, Li-Wei
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Lin, Chin-Teng
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Ge, Zheng-Ming
We expose the chaotic attractors of time-reversed nonlinear system, further implement its behavior on electronic circuit, and apply the pragmatical asymptotically stability theory to strictly prove that the adaptive synchronization of given master and slave systems with uncertain parameters can be achieved. In this paper, the variety chaotic motions of time-reversed Lorentz system are investigated through Lyapunov exponents, phase portraits, and bifurcation diagrams. For further applying the complex signal in secure communication and file encryption, we construct the circuit to show the similar chaotic signal of time-reversed Lorentz system. In addition, pragmatical asymptotically stability theorem and an assumption of equal probability for ergodic initial conditions (Ge et al., 1999, Ge and Yu, 2000, and Matsushima, 1972) are proposed to strictly prove that adaptive control can be accomplished successfully. The current scheme of adaptive control-by traditional Lyapunov stability theorem and Barbalat lemma, which are used to prove the error vector-approaches zero, as time approaches infinity. However, the core question-why the estimated or given parameters also approach to the uncertain parameters-remains without answer. By the new stability theory, those estimated parameters can be proved approaching the uncertain values strictly, and the simulation results are shown in this paper.
Novel Fuzzy Modeling and Synchronization of Chaotic Systems With Multinonlinear Terms by Advanced Ge-Li Fuzzy Model
(2016-10)
Li, Shih-Yu
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Tam, Lap-Mou
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Tsai, Shang-En
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Ge, Zheng-Ming
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機械工程學系
Ge and Li proposed an alternative strategy to model and synchronize two totally different nonlinear systems in the end of 2011, which provided a new version for fuzzy modeling and has been applied to several fields to simplify their modeling works and solve the mismatch problems [1]-[17]. However, the proposed model limits the number of nonlinear terms in each equation so that this model could not be used in all kinds of nonlinear dynamic systems. As a result, in this paper, a more efficient and comprehensive advanced-Ge-Li fuzzy model is given to further release the limitation and improve the effectiveness of the original one. The novel fuzzy model can be applied to all kinds of complex nonlinear systems-this is the universal strategy and only m x 2 fuzzy rules as well as two linear subsystems are needed to simulate nonlinear behaviors (m is the number of states in a nonlinear dynamic system), whatever the nonlinear terms are copious or complicated. Further, the fuzzy synchronization of two nonlinear dynamic systems with totally distinct structures can be achieved via only two sets of control gains designed through the novel fuzzy model as well as its corresponding fuzzy synchronization scheme. Two complicated dynamic systems are designed to be the illustrations, Mathieu-Van der pol system with uncertainties and Quantum-cellular neural networks nano system with uncertainties, to show the effectiveness and feasibility of the novel fuzzy model.