Showing papers in "Nonlinear Dynamics in 2014"

Discrete fractional logistic map and its chaos

Abstract: A discrete fractional logistic map is proposed in the left Caputo discrete delta’s sense. The new model holds discrete memory. The bifurcation diagrams are given and the chaotic behaviors are numerically illustrated.

Hidden oscillations in mathematical model of drilling system actuated by induction motor with a wound rotor

Abstract: This work is devoted to the investigation of mathematical models of drilling systems described by ordinary differential equations. Here, we continue the study done by the researchers from Eindhoven where the two-mass mathematical model of a drilling system has been investigated (Mihajlovic et al. J. Dyn. Syst. Meas. Control 126(4): 709–720, 2004; de Bruin et al. Automatica 45(2): 405–415, 2009). The modified version of this model, which takes into account a full description of an induction motor, is studied. It is shown that such complex effects as hidden oscillations may appear in these kinds of systems. These effects may lead to drill string failures and breakdowns.

Global Mittag-Leffler stability and synchronization of impulsive fractional-order neural networks with time-varying delays

Abstract: In this paper we consider a class of impulsive Caputo fractional-order cellular neural networks with time-varying delays. Applying the fractional Lyapunov method and Mittag-Leffler functions, we give sufficient conditions for global Mittag-Leffler stability which implies global asymptotic stability of the network equilibrium. Our results provide a design method of impulsive control law which globally asymptotically stabilizes the impulse free fractional-order neural network time-delay model. The synchronization of fractional chaotic networks via non-impulsive linear controller is also considered. Illustrative examples are given to demonstrate the effectiveness of the obtained results.

A new car-following model with consideration of inter-vehicle communication

Abstract: In this paper, we construct a new car-following model with inter-vehicle communication (IVC) to study the driving behavior under an accident. The numerical results show that the proposed model can qualitatively describe the effects of IVC on each vehicle’s speed, acceleration, movement trail, and headway under an accident and that the new model can overcome the full velocity difference (FVD) model’s shortcoming that collisions occur under an accident, which illustrates that the new model can better describe the driving behavior under an accident than the FVD model.

Piezoelectric energy harvesting from concurrent vortex-induced vibrations and base excitations

Abstract: We investigate the potential of using a piezoelectric energy harvester to concurrently harness energy from base excitations and vortex-induced vibrations. The harvester consists of a multilayered piezoelectric cantilever beam with a circular cylinder tip mass attached to its free end which is placed in a uniform air flow and subjected to direct harmonic excitations. We model the fluctuating lift coefficient by a van der Pol wake oscillator. The Euler–Lagrange principle and the Galerkin procedure are used to derive a nonlinear distributed-parameter model for a harvester under a combination of vibratory base excitations and vortex-induced vibrations. Linear and nonlinear analyses are performed to investigate the effects of the electrical load resistance, wind speed, and base acceleration on the coupled frequency, electromechanical damping, and performance of the harvester. It is demonstrated that, when the wind speed is in the pre- or post-synchronization regions, its associated electromechanical damping is increased and hence a reduction in the harvested power is obtained. When the wind speed is in the lock-in or synchronization region, the results show that there is a significant improvement in the level of the harvested power which can attain 150 % compared to using two separate harvesters. The results also show that an increase of the base acceleration results in a reduction in the vortex-induced vibrations effects, an increase of the difference between the resonant excitation frequency and the pull-out frequency, and a significant effects associated with the quenching phenomenon.

Selection of multi-scroll attractors in Jerk circuits and their verification using Pspice

Abstract: In this paper, a feasible feedback scheme is used to stabilize the multi-scroll attractors in the Jerk circuit, and the controller is realized using mixed Heaviside function. It is found that arbitrary number (\(n=2, 3, 4, 5,{\ldots }\)) of multi-scroll attractors can be selected from a controlled Jerk circuit, and these multi-scroll attractors can be reproduced using Pspice. The implementation of circuit and controller using Pspice is also presented. The potential mechanism could be that an external forcing in the Sine type is practical to generate a group of equilibrium points, and a linear controller composed of Heaviside function is effective to stabilize the \(n\)-scroll attractors in the chaotic systems.

Finite-time stability analysis of fractional-order complex-valued memristor-based neural networks with time delays

Abstract: In this paper, the problem of finite-time stability of fractional-order complex-valued memristor-based neural networks (NNs) with time delays is extensively investigated. We first initiate the fractional-order complex-valued memristor-based NNs with the Caputo fractional derivatives. Using the theory of fractional-order differential equations with discontinuous right-hand sides, Laplace transforms, Mittag-Leffler functions and generalized Gronwall inequality, some new sufficient conditions are derived to guarantee the finite-time stability of the considered fractional-order complex-valued memristor-based NNs. In addition, some sufficient conditions are also obtained for the asymptotical stability of fractional-order complex-valued memristor-based NNs. Finally, a numerical example is presented to demonstrate the effectiveness of our theoretical results.

Finite-time synchronization control for uncertain Markov jump neural networks with input constraints

Abstract: This paper is concerned with the problem of finite-time synchronization control for uncertain Markov jump neural networks in the presence of constraints on the control input amplitude. The parameter uncertainties under consideration are assumed to belong to a fixed convex polytope. By using a parameter-dependent Lyapunov functional and a simple matrix decoupling method, a sufficient condition is proposed to ensure that the considered networks are stochastically synchronized over a finite-time interval. The desired mode-independent controller parameters can be computed via solving a convex optimization problem. Finally, two chaos neural networks are employed to demonstrate the effectiveness of our proposed approach.

Robust adaptive dynamic surface control design for a flexible air-breathing hypersonic vehicle with input constraints and uncertainty

Abstract: The flight control problem of a flexible air-breathing hypersonic vehicle is presented in the presence of input constraint and aerodynamic uncertainty. A control-oriented model, where aerodynamic uncertainty and the strong couplings between the engine and flight dynamics are included, is derived to reduce the complexity of controller design. The flexible dynamics are viewed as perturbations of the model. They are not taken into consideration at the level of control design, the influence of which is evaluated through simulation. The control-oriented model is decomposed into velocity subsystem and altitude subsystem, which are controlled separately. Then robust adaptive controller is developed for the velocity subsystem, while the controller which combines dynamic surface control and radial basis function neural network is designed for the altitude subsystem. The unknown nonlinear function is approximated by the radial basis function neural network. Minimal-learning parameter technique is utilized to estimate the maximum norm of ideal weight vectors instead of their elements to reduce the computational burden. To handle input constraints, additional systems are constructed to analyze their impact, and the states of the additional systems are employed at the level of control design and stability analysis. Besides, “explosion of terms” problem in the traditional backstepping control is circumvented using a first-order filter at each step. By means of Lyapunov stability theory, it is proved theoretically that the designed control law can assure that tracking error converges to an arbitrarily small neighborhood around zero. Simulations are performed to demonstrate the effectiveness of the presented control scheme in coping with input constraint and aerodynamic uncertainty.

Biological experimental demonstration of bifurcations from bursting to spiking predicted by theoretical models

Abstract: A series of bifurcations from period-1 bursting to period-1 spiking in a complex (or simple) process were observed with increasing extra-cellular potassium concentration during biological experiments on different neural pacemakers. This complex process is composed of three parts: period-adding sequences of burstings, chaotic bursting to chaotic spiking, and an inverse period-doubling bifurcation of spiking patterns. Six cases of bifurcations with complex processes distinguished by period-adding sequences with stochastic or chaotic burstings that can reach different bursting patterns, and three cases of bifurcations with simple processes, without the transition from chaotic bursting to chaotic spiking, were identified. It reveals the structures closely matching those simulated in a two-dimensional parameter space of the Hindmarsh–Rose model, by increasing one parameter $$I$$ and fixing another parameter $$r$$ at different values. The experimental bifurcations also resembled those simulated in a physiologically based model, the Chay model. The experimental observations not only reveal the nonlinear dynamics of the firing patterns of neural pacemakers but also provide experimental evidence of the existence of bifurcations from bursting to spiking simulated in the theoretical models.

Analyses of the driver's anticipation effect in a new lattice hydrodynamic traffic flow model with passing

Abstract: In this paper, we studied the effect of driver’s anticipation with passing in a new lattice model. The effect of driver’s anticipation is examined through linear stability analysis and shown that the anticipation term can significantly enlarge the stability region on the phase diagram. Using nonlinear stability analysis, we obtained the range of passing constant for which kink soliton solution of mKdV equation exist. For smaller values of passing constant, uniform flow and kink jam phase are present on the phase diagram and jamming transition occurs between them. When passing constant is greater than the critical value depending on the anticipation coefficient, jamming transitions occur from uniform traffic flow to kink-bando traffic wave through chaotic phase with decreasing sensitivity. The theoretical findings are verified using numerical simulation which confirm that traffic jam can be suppressed efficiently by considering the anticipation effect in the new lattice model.

Highly efficient nonlinear energy sink

Abstract: The performance of the nonlinear energy sink (NES) that composed of a small mass and essentially nonlinear coupling stiffness with a linear structure is considerably enhanced here by including the negative linear and nonlinear coupling stiffness components. These negative linear and nonlinear stiffness components in the NES are realized here through the geometric nonlinearity of the transverse linear springs. By considering these components in the NES, very intersecting results for passive targeted energy transfer (TET) are obtained. The performance of this modified NES is found here to be much improved than that of all existing NESs studied up to date in the literature. Moreover, nearly 99 % of the input shock energy induced by impulse into the linear structures considered here has been found to be rapidly transferred and locally dissipated by the modified NES. In addition, this modified NES maintains its high performance of shock mitigation in a broadband fashion of the input initial energies where it keeps its high performance even for sever input energies. This is found to be achieved by an immediate cascade of several resonance captures at low- and high- nonlinear normal modes frequencies. The findings obtained here by including the negative linear and nonlinear stiffness components are expected to significantly enrich the application of these stiffness components in the TET field of such nonlinear oscillators.

Second-order sliding-mode controller for autonomous underwater vehicle in the presence of unknown disturbances

Abstract: We propose the use of a second-order sliding-mode controller (2-SMC) to stabilize an autonomous underwater vehicle (AUV) which is subject to modeling errors and often suffers from unknown environmental disturbances. The 2-SMC is effective in compensating for the uncertainties in the hydrodynamic and hydrostatic parameters of the vehicle and rejecting the unpredictable disturbance effects due to ocean waves, tides, and currents. The 2-SMC is comprised of an equivalent controller and a switching controller to suppress the parameter uncertainties and external disturbances, and its closed-loop system is exponentially stable in the presence of parameter uncertainties and unknown disturbances. We performed numerical simulations to validate the proposed control approach, and experimental tests using Cyclops AUV were conducted to demonstrate its practical feasibility. The proposed controller increased the accuracy of trajectory tracking for an AUV in the presence of uncertain hydrodynamics and unknown disturbances.

A fast color image encryption algorithm based on hyper-chaotic systems

Abstract: This paper presents a new way of image encryption scheme, which consists of two processes; key stream generation process and one-round diffusion process. The first part is a pseudo-random key stream generator based on hyper-chaotic systems. The initial conditions for both hyper-chaotic systems are derived using a 256-bit-long external secret key by applying some algebraic transformations to the key. The original key stream is related to the plain-image which increases the level of security and key sensitivity of the proposed algorithm. The second process employs the image data in order to modify the pixel gray-level values and crack the strong correlations between adjacent pixels of an image simultaneously. In this process, the states which are combinations of two hyper-chaotic systems are selected according to image data itself and are used to encrypt the image. This feature will significantly increase plaintext sensitivity. Moreover, in order to reach higher security and higher complexity, the proposed method employs the image size in key stream generation process. It is demonstrated that the number of pixel change rate (NPCR) and the unified average changing intensity (UACI) can satisfy security and performance requirements (NPCR $$>$$ 99.80 %, UACI $$>$$ 33.56 %) in one round of diffusion. The experimental results reveal that the new image encryption algorithm has the advantages of large key space, high security, high sensitivity, and high speed. Also, the distribution of gray-level values of the encrypted image has a semi-random behavior.

A new image alternate encryption algorithm based on chaotic map

Abstract: In this paper, a new image alternative encryption algorithm is proposed, in which the shuffling and diffusion are performed simultaneously. The plain image is divided into two left and right blocks of same size. The matrix which is generated by a logistic map is used to diffuse the left block of the plain image. Then, the diffused image is used as the right block of the cipher image. The 0, 1 sequence which comes from another logistic chaotic sequence and plaintext is used to shuffle the right block of the cipher image. After the operation XOR, the left block of cipher image is generated. Finally, two new-generated blocks are merged into the cipher image. In order to get better effect for image encryption, this process can be repeated many rounds. The simulation results show that this algorithm has properties of big key space, high sensitivity to key, resisting statistical analysis, differential attacks, plaintext attacks, and chosen-plaintext attacks. So, it has high security and can be suitable for image encryption.

A novel image encryption algorithm based on dynamic S-boxes constructed by chaos

Abstract: In this manuscript, an image encryption based on dynamic S-boxes is presented, in which the S-boxes are constructed by chaotic systems. An external 256-bit key and the last pixel of plain image are used to generate the parameters and initial states of the chaotic systems for the first S-box. The plain image is divided into groups in which the pixels are substituted by S-boxes and in order to smash the correlation of adjacent pixels the image is grouped in four directions. After encrypting previous group, the initial states of chaotic systems are altered by encrypted image pixels and the S-box for the next group is generated. This algorithm scheme can make it resist differential attacks and chosen plain-text attacks. Moreover, because in the all process we only need to construct less than 50 S-boxes, the progress time is reduced. Superiority in speed and security is analyzed by applying the algorithm on 256-grey images.

Analysis and improvement of a chaos-based symmetric image encryption scheme using a bit-level permutation

Abstract: Recently, a chaos-based symmetric image encryption scheme using a bit-level permutation was proposed. In this paper, we analyze the potential flaws in Zhu’s algorithm in detail and develop a chosen-plaintext attack and chosen-ciphertext attack on Zhu’s algorithm. The proposed attack indicates that the Arnold cat map applied directly in image encryptions is not suitable for cryptography. We also propose the corresponding improved scheme. The improved scheme preserves the merits of the original one.

Global bifurcation and chaos analysis in nonlinear vibration of spur gear systems

Abstract: The global homoclinic bifurcation and transition to chaotic behavior of a nonlinear gear system are studied by means of Melnikov analytical analysis. It is also an effective approach to analyze homoclinic bifurcation and detect chaotic behavior. A generalized nonlinear time varying (NLTV) dynamic model of a spur gear pair is formulated, where the backlash, time varying stiffness, external excitation, and static transmission error are included. From Melnikov method, the threshold values of the control parameter for the occurrence of homoclinic bifurcation and onset of chaos are predicted. Additionally, the numerical bifurcation analysis and numerical simulation of the system including bifurcation diagrams, phase plane portraits, time histories, power spectras, and Poincare sections are used to confirm the analytical predictions and show the transition to chaos.

Airship horizontal trajectory tracking control based on Active Disturbance Rejection Control (ADRC)

Abstract: Aiming at flight property of airship, a trajectory tracking controller of airship horizontal model is designed based on active disturbance rejection control (ADRC). The six Degree of Freedom (DOF) dynamic model of airship is simplified at a horizontal plane. ADRC is used to realize the decoupling control for the multivariable system. The uncertain items of the model and external disturbances are estimated by the extended state observer (ESO) and dynamic feedback compensation is carried on at real time. The disturbance of wind is added to the simulation environment. The simulation results show that the designed tracking controller can overcome the influences of uncertain items of the model and external disturbances, and track the desired trajectory rapidly and steadily, and possess good robustness and control performances.

Cryptanalyzing image encryption using chaotic logistic map

Abstract: Chaotic behavior arises from very simple non-linear dynamical equation of logistic map which makes it was used often in designing chaotic image encryption schemes. However, some properties of chaotic maps can also facilitate cryptanalysis especially when they are implemented in digital domain. Utilizing stable distribution of the chaotic states generated by iterating the logistic map, this paper presents a typical example to show insecurity of an image encryption scheme using chaotic logistic map. This work will push encryption and chaos be combined in a more effective way.

Anti-synchronization between identical and non-identical fractional-order chaotic systems using active control method

Abstract: This article deals with the anti-synchronization between two identical chaotic fractional-order Qi system, Genesio–Tesi system, and also between two different fractional-order Genesio–Tesi and Qi systems using active control method. The chaotic attractors of the systems are found for fractional-order time derivatives described in Caputo sense. Numerical simulation results which are carried out using Adams–Boshforth–Moulton method show that the method is reliable and effective for anti-synchronization of nonlinear dynamical evolutionary systems.

A novel image encryption scheme based on Brownian motion and PWLCM chaotic system

Abstract: Many encryption algorithms are directly based on the matrix transformation or their own definition of strict rules. We try to propose a new digital image encryption scheme to simulate physical phenomena rather than deliberately create rigid rules. First, the paper takes each pixel of the image as a Brownian particle, using the Monte Carlo method to simulate a Brownian motion, thus effectively scrambling the image. Then we diffuse the image with PWLCM chaotic system. To enhance the sensitivity of the key and the plaintext, we modified the initial value of PWLCM chaotic system. Experimental results and security analysis show that our method has good performance and can be used in image encryption and transmission.

A general mechanism to generate three limit cycles in planar Filippov systems with two zones

Abstract: Discontinuous piecewise linear systems with two zones are considered. A general canonical form that includes all the possible configurations in planar linear systems is introduced and exploited. It is shown that the existence of a focus in one zone is sufficient to get three nested limit cycles, independently on the dynamics of the another linear zone. Perturbing a situation with only one hyperbolic limit cycle, two additional limit cycles are obtained by using an adequate parametric sector of the unfolding of a codimension-two focus-fold singularity.

New augmented Lyapunov–Krasovskii functional approach to stability analysis of neural networks with time-varying delays

Abstract: This paper is concerned with the problem of stability analysis for neural networks with time-varying delays. By constructing a newly augmented Lyapunov functional and some novel techniques, delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). The improvement of feasible region of the proposed criteria comparing with the previous works is shown by two numerical examples.

New results on stability and stabilization of a class of nonlinear fractional-order systems

Abstract: The asymptotic stability and stabilization problem of a class of fractional-order nonlinear systems with Caputo derivative are discussed in this paper. By using of Mittag–Leffler function, Laplace transform, and the generalized Gronwall inequality, a new sufficient condition ensuring local asymptotic stability and stabilization of a class of fractional-order nonlinear systems with fractional-order α:1<α<2 is proposed. Then a sufficient condition for the global asymptotic stability and stabilization of such system is presented firstly. Finally, two numerical examples are provided to show the validity and feasibility of the proposed method.

Spatio-temporal dynamics of a reaction-diffusion system for a predator–prey model with hyperbolic mortality

Abstract: We investigate the effects of diffusion on the spatial dynamics of a predator–prey model with hyperbolic mortality in predator population. More precisely, we aim to study the formation of some elementary two-dimensional patterns such as hexagonal spots and stripe patterns. Based on the linear stability analysis, we first identify the region of parameters in which Turing instability occurs. When control parameter is in the Turing space, we analyse the existence of stable patterns for the excited model by the amplitude equations. Then, for control parameter away from the Turing space, we numerically investigate the initial value-controlled patterns. Our results will enrich the pattern dynamics in predator–prey models and provide a deep insight into the dynamics of predator–prey interactions.

An efficient and provably secure three-party password-based authenticated key exchange protocol based on Chebyshev chaotic maps

Abstract: Three-party password-based authenticated key exchange (3PAKE) protocols allow two clients to establish a secure session key through a server over an insecure channel. Recently, the 3PAKE protocols have been developed based on Chebyshev chaotic maps, in which the clients utilize smart cards to login into the server and employ server’s public key to ensure the identity of the server or symmetric cryptosystems to encrypt the messages. However, this paper describes an efficient chaos-based 3PAKE protocol without smart cards, which requires neither server’s public key nor symmetric cryptosystems. The security of the proposed 3PAKE protocol is proved in the random oracle model using the chaos-based decisional Diffie–Hellman assumption. In comparison with the existing chaos-based 3PAKE protocols, our protocol individually provides better performance in terms of communication, computation, and security aspects, and is supported by the formal proof in the random oracle model.

On hidden twin attractors and bifurcation in the Chua’s circuit

Abstract: Recently a new attractor, called hidden attractor, has been found in the well-known Chua’s circuit, whose basin of attraction does not contain neighborhood of any equilibrium. This paper will restudy this circuit, showing that two hidden attractors can coexist in this circuit for some parameters, and characterizes the basins of these two attractors by means of computer method as well. In addition, a computer-assisted proof of the chaoticity of these attracters is presented by a topological horseshoe theory.

Implementation of FPGA-based real time novel chaotic oscillator

Abstract: Currently, chaotic systems and chaos-based applications are commonly used in the engineering fields. One of the main structures used in these applications is the chaos-based signal generators. Chaotic signal generators have an important role, particularly in chaotic communication and cryptology. In this study, the Pehlivan-Wei chaotic system, which is a recently developed chaotic system, has been implemented with FPGA using three distinct algorithms (the Euler, Heun, and RK4) for the first time in literature. Numerical and HDL approaches are implemented by these three algorithms to compare the performance of each model for use in chaotic generators. In addition, the Lyapunov exponents and phase portraits of the system have been extracted for chaos analysis. RMSE analysis has been conducted on the chaotic generators, which are modeled using the Euler, Heun, and RK4 algorithms in order to observe error rates of each numerical algorithm in a comparative aspect. The performance of new chaotic system with various data sets has been analyzed. The operation frequency of the chaotic oscillators synthesized and tested for the Virtex-6 FPGA chip has been able to reach up to 463.688 MHz and the chaotic system has been able to calculate 300,000 data sets in 0.0284 s. However, PC-based algorithm having highest performance score can calculate 300,000 data sets in a period of 75.363 s. A comparison study has been performed on the performance of the FPGA-based and PC-based solutions to evaluate each approach.

Several gradient-based iterative estimation algorithms for a class of nonlinear systems using the filtering technique

Abstract: This paper considers iterative identification problems for a class of nonlinear systems with colored noises, which can be described by a linear-in-parameters output error autoregressive model. A gradient-based iterative (GI) algorithm, a filtered GI algorithm, and a filtered three-stage GI algorithm are developed using the decomposition technique and filtering technique, and their computational efficiencies are analyzed and compared. The simulation results indicate that the proposed algorithms can estimate effectively the parameters of nonlinear systems.