Synchronization of nonlinear chaotic electromechanical gyrostat systems with uncertainties

This paper solves the problem of robust synchronization of nonlinear chaotic gyrostat systems in a given finite time. The parameters of both master and slave chaotic gyrostat systems are assumed to be unknown in advance. In addition, the gyrostat systems are disturbed by unknown model uncertainties and external disturbances. Suitable update laws are proposed to estimate the unknown parameters. Based on the finite-time control idea and update laws, appropriate control laws are designed to ensure the stabilization of the closed-loop system in finite time. The precise value of the convergence time is given. A numerical simulation demonstrates the applicability and efficiency of the proposed finite-time synchronization strategy.     

Adaptive finite-time stabilization of uncertain non-autonomous chaotic electromechanical gyrostat systems with unknown parameters

This paper deals with the problem of robust finite-time stabilization of non-autonomous chaotic gyrostat systems. It is assumed that the parameters of the gyrostat system are completely unknown in advance and the system is perturbed by unknown uncertainties and disturbances. Some update laws are proposed to estimate the unknown parameters. Based on the finite-time control idea and the update laws, appropriate control laws are designed to ensure the stabilization of the closed-loop system in a finite time. The finite-time stability and convergence of the closed-loop system are analytically proved. A numerical simulation is given to demonstrate the applicability and robustness of the proposed finite-time controller and to verify the theoretical results.     

Finite-time stabilization of uncertain non-autonomous chaotic gyroscopes with nonlinear inputs

Gyroscopes are one of the most interesting and everlasting nonlinear nonautonomous dynamical systems that exhibit very complex dynamical behavior such as chaos.In this paper,the problem of robust stabi...     

Generalized finite-time synchronization between coupled chaotic systems of different orders with unknown parameters

This letter investigates the adaptive finite-time synchronization of different coupled chaotic (or hyperchaotic) systems with unknown parameters. The sufficient conditions for achieving the generalized finite-time synchronization of two chaotic systems are derived based on the theory of finite-time stability of dynamical systems. By the adaptive control technique, the control laws and the corresponding parameters update laws are proposed such that the generalized finite-time synchronization of nonidentical chaotic (or hyperchaotic) systems is to be obtained. These results obtained are in good agreement with the existing one in open literature and it is shown that the technique introduced here can be further applied to various finite-time synchronizations between dynamical systems. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed scheme.     

A projective synchronization scheme based on fuzzy adaptive control for unknown multivariable chaotic systems

In this paper, a projective synchronization problem of master–slave chaotic systems is investigated. More specifically, a fuzzy adaptive controller is investigated for a projective synchronization of uncertain multivariable chaotic systems. The adaptive fuzzy-logic systems are used to approximate the unknown functions. A decomposition property of the control gain matrix is used in the controller design and the stability analysis. A Lyapunov approach is employed to derive the parameter adaptation laws and prove the boundedness of all signals of the closed-loop system as well as the exponential convergence of the synchronization errors to an adjustable region. Numerical simulations are performed to verify the effectiveness of the proposed synchronization scheme.     

Robust adaptive synchronization for a class of chaotic systems with actuator failures and nonlinear uncertainty

This paper is concerned with the robust adaptive synchronization problem for a class of chaotic systems with actuator failures and unknown nonlinear uncertainty. Combining adaptive method and linear matrix inequality (LMI) technique, a novel type of robust adaptive reliable synchronization controller is proposed, which can eliminate the effect of actuator fault and nonlinear uncertainty on systems. After solving a set of LMIs, synchronization error between the master chaotic and slave chaotic systems can converge asymptotically to zero. Finally, illustrate examples about chaotic Chua’s circuit system and Lorenz systems are provided to demonstrate the effectiveness and applicability of the proposed design method.     

Finite-time combination-combination synchronization of four different chaotic systems with unknown parameters via sliding mode control

In this paper, we apply the nonsingular terminal sliding mode control technique to realize the novel combination-combination synchronization between combination of two chaotic systems as drive system and combination of two chaotic systems as response system with unknown parameters in a finite time. On the basic of the adaptive laws and finite-time stability theory, an adaptive combination sliding mode controller is proposed to ensure the occurrence of the sliding motion in a given finite time for four different chaotic systems. In theory, it is proved that the sliding mode technique can realize fast convergence for four different chaotic systems in the finite time. Some criteria and corollaries are derived for finite-time combination-combination synchronization of four different chaotic systems. Numerical simulation results are shown to verify the effectiveness and correctness of the combination-combination synchronization.     

Spatiotemporal combination synchronization of different nonlinear objects

This paper proposes a novel secure communication scheme based on the Karhunen–Loéve decomposition and the synchronization of a master and a slave hyperchaotic Lü systems. First, the Karhunen–Loéve decomposition is used as a data reduction tool to generate data coefficients and eigenfunctions that capture the essence of grayscale and color images in an optimal manner. It is noted that the original images can be reproduced using only the most energetic eigenfunctions; this results in computational savings. The data coefficients are encrypted and transmitted using a master hyperchaotic Lü system. These coefficients are then recovered at the receiver end using a sliding mode controller to synchronize two hyperchaotic Lü systems. Simulation results are presented to illustrate the ability of the proposed control law to synchronize the master and slave hyperchaotic Lü systems. Moreover, the original images are recovered by using the decrypted data coefficients in conjunction with the eigenfunctions of the image. Computer simulation results are provided to show the excellent performance of the proposed scheme.     

Adaptive neural network control of bilateral teleoperation with constant time delay

This paper proposes a novel approach for bilateral teleoperation systems with a multi degrees-of-freedom (DOF) nonlinear robotic system on the master and slave side with constant time delay in a communication channel. We extend the passivity based architecture to improve position and force tracking and consequently transparency in the face of offset in initial conditions, environmental contacts and unknown parameters such as friction coefficients. The proposed controller employs a stable neural network on each side to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitations of conventional controllers such as PD or adaptive controllers and guaranteeing good tracking performance. Moreover, we show that this new neural network controller preserves the control passivity of the system. Simulation results show that NN controller tracking performance is superior to that of conventional controllers.     

Adaptive fuzzy synchronization for a class of chaotic systems with unknown nonlinearities and disturbances

By incorporating a time-varying parameter into T-S fuzzy logic systems with nonlinear consequents (T-S-FLS-NRC), the synchronization of driver-response chaotic systems with unknown nonlinearities and disturbances is synthesized via state feedback controllers and updated adaptive laws. During designing process of synchronization, only three common parameters are needed to be adjusted automatically, and the number of adaptive laws is not related with the number of IF-THEN rules. Meanwhile, T-S-FLS-NRC is employed to approximate the unknown nonlinearities for the master and slave systems. The general form and high approximate capacity of T-S-FLS-NRC is useful to obtain fewer fuzzy rules than other fuzzy logic systems such as Mamdani or T-S fuzzy logic system with linear consequents. The synchronization method in this paper cannot only significantly reduce the on-line computational burden, but also can synthesize the fuzzy rules with high interpretability by means of intuition inferences. Finally, a numerical example is used to show the validity of the proposed synchronization method.     

Robust synchronization of uncertain fractional-order chaotic systems with time-varying delay

This paper presents a new technique using a recurrent non-singleton type-2 sequential fuzzy neural network (RNT2SFNN) for synchronization of the fractional-order chaotic systems with time-varying delay and uncertain dynamics. The consequent parameters of the proposed RNT2SFNN are learned based on the Lyapunov–Krasovskii stability analysis. The proposed control method is used to synchronize two non-identical and identical fractional-order chaotic systems, with time-varying delay. Also, to demonstrate the performance of the proposed control method, in the other practical applications, the proposed controller is applied to synchronize the master–slave bilateral teleoperation problem with time-varying delay. Simulation results show that the proposed control scenario results in good performance in the presence of external disturbance, unknown functions in the dynamics of the system and also time-varying delay in the control signal and the dynamics of system. Finally, the effectiveness of proposed RNT2SFNN is verified by a nonlinear identification problem and its performance is compared with other well-known neural networks.     

Robust synchronization of nonlinear SISO systems using sliding mode control

We present a robust algorithm to synchronize two different single-input/single-output (SISO) nonlinear systems connected in a master/slave scheme, where the relative degree of the master system (r _m) is greater than or equal to the relative degree of the slave (r _s). The sliding mode control technique is used to design the coupling signal. This discontinuous controller renders the closed-loop system robust with respect to matched bounded disturbances. The synchronization objective is to match the first r _s normal coordinates. Depending on the characteristics of the involved systems, the closed loop system can display full or partial, identical or generalized synchronization. The performance of the proposed controlled synchronization is illustrated numerically and experimentally.     

Adaptive synchronization of the energy resource systems with mismatched parameters via linear feedback control

Synchronization of energy resource systems with mismatched parameters is investigated. An adaptive linear feedback control scheme for the synchronization of energy resource systems is proposed when the parameters of the master system are unknown and different from those of the slave system. Based on the Lyapunov stability theory, an adaptive control law is derived to make the states of two slightly mismatched chaotic systems asymptotically synchronized. Finally, numerical simulations are performed to verify the proposed results.     

Synchronization of master–slave Lagrangian systems via intermittent control

In this paper, synchronization of master–slave Lagrangian systems via intermittent control was developed. Based on the intermittent control, some algebraic criteria are derived to make the slave Lagrangian system synchronize to a master one. Different from the most existing results on control problems of Lagrangian systems, the controller proposed here is not continuous-time control input and is not relied on the knowledge of system models. As a direct application, the obtained results are applied to a typical two-link revolute jointed robot (robot manipulator). Subsequently, numerical simulations demonstrate the effectiveness of the criteria and the robustness of the control strategy.     

Finite-time non-fragile boundary feedback control for a class of nonlinear parabolic systems

In this paper, the finite-time non-fragile boundary feedback control problem is investigated for a class of nonlinear parabolic systems, where both the multiplicative and additive controller gain variations are considered to describe the actuator parameter perturbation. Non-fragile boundary control strategies are designed with respect to two controller gain variations via collocated or non-collocated boundary measurement, respectively. In light of the finite-time stability and Lyapunov-based techniques, some sufficient conditions are presented in terms of linear matrix inequalities such that the resulting closed-loop system is well-posedness and practically finite-time stable. Finally, numerical examples are given to verify the effectiveness of the proposed design method.

     

Robust synchronization of a chaotic mechanical system with nonlinearities in control inputs

Centrifugal flywheel governors are known as chaotic non-autonomous mechanical devices used for automatic control of the speed of engines. The main characteristic of them is avoiding the damage caused by sudden change of the load torques. In this paper, the problem of robust finite-time synchronization of centrifugal flywheel governor systems is studied. The effects of unknown parameters, model uncertainties, external noises, and input nonlinearities are fully taken into account. We propose some adaptive laws to overcome the side effects of the unknown parameters of the system on the synchronization performance. Then, a robust adaptive switching controller is introduced to synchronize centrifugal flywheel governors with nonlinear control inputs in a given finite time. The finite-time fast convergence property of the proposed scheme is analytically proved and numerically illustrated.     

Multi-switching synchronization of chaotic system with adaptive controllers and unknown parameters

Using adaptive control techniques, we investigate the multi-switching synchronization of chaotic systems with parameters unknown. Based upon the Lyapunov stability theory, we design the controllers and updating laws of different switching, and it is extended to investigate the synchronization problems with different combinations of slave states with master systems. We take the Lorenz system and the Chen system as an example to analyze the multi-switching synchronization process of different structures of chaotic systems. Finally, numerical simulations have shown the effectiveness of the method.     

Adaptive modified function projective synchronization and parameter identification of uncertain hyperchaotic (chaotic) systems with identical or non-identical structures

Modified function projective synchronization (MFPS), which generalizes many kinds of synchronization form, has received great attention recently. Based on the active control method and adaptive control technique, a general formula for designing the controllers is proposed to achieve adaptive MFPS, which corrects several incomplete results that have been reported recently. In addition, this paper derives the sufficient condition for parameter identification, which was not mentioned in much of the relevant literature concerning MFPS. Furthermore, we extend the MFPS scheme to the cases that the drive and response systems come with non-identical structures. The proposed method is both theoretically rigorous and practically feasible, which has the merits that it can not only achieve the full-state MFPS but also identify the fully unknown parameters in the synchronization process. The theoretical results are successfully applied to three typical illustrative cases: the adaptive MFPS of two identical 4-D hyperchaotic systems with unknown parameters in the response system, the adaptive MFPS between a 5-D hyperchaotic system and a 4-D hyperchaotic system with unknown parameters in the drive system and the adaptive MFPS between a 3-D chaotic system and a 4-D hyperchaotic system when the parameters in the drive system and response system are all unknown. For each case the controller functions and parameter update laws are well designed in detail. Moreover, the corresponding numerical simulations are presented, which agree well with the theoretical analysis.     

Chaos suppression of rotational machine systems via finite-time control method

This paper introduces an adaptive control scheme for chaos suppression of non-autonomous chaotic rotational machine systems with fully unknown parameters in finite time. To estimate the system unknown parameters, some adaptation laws are proposed. Using the adaptation laws and Lyapunov control theory, an adaptive robust controller is derived to suppress the chaos of non-autonomous centrifugal flywheel governor systems in a given finite time. Some mathematical approaches are presented to prove the finite-time stability and convergence of the proposed method. The exact value of the convergence time is also given. A numerical simulation is provided to illustrate the usefulness and effectiveness of the introduced algorithm and to verify the theoretical results of the paper.     

Finite-time chaos control of unified chaotic systems with uncertain parameters

This paper is concerned with finite-time chaos control of unified chaotic systems with uncertain parameters. Based on the finite-time stability theory in the cascade-connected system, a nonlinear control law is presented to achieve finite-time chaos control. The controller is simple and easy to be constructed. Simulation results for Lorenz, Lü, and Chen chaotic systems are provided to illustrate the effectiveness of the proposed scheme. Supported by the National Natural Science Foundation of China (Grant No. 60674024).