Adaptive Synchronization Research Articles

Adaptive Practical Fixed-Time Synchronization Control for Bilateral Teleoperation System With Prescribed Performance

In this brief, an adaptive practical fixed-time synchronization control scheme for position tracking of a bilateral teleoperation system with prescribed performance is proposed. A prescribed performance function (PPF) is incorporated into the fixed-time control framework such that the synchronization errors will converge into a residual set in a fixed time and the upper bound of setting time is regardless of the initial states. The upper bound of system uncertainties is estimated via adaptive technique such that the adverse effect induced by system uncertainties can be attenuated. Simulation studies and experiments demonstrate the effectiveness and practicality of the proposed control scheme in terms of both transient and steady-state performance.

Neural network-based adaptive synchronization for second-order nonlinear multiagent systems with unknown disturbance.

This paper handles the distributed adaptive synchronization problem for a class of unknown second-order nonlinear multiagent systems subject to external disturbance. It is supposed to be an unknown one for the underlying external disorder. First, the neural network-based disturbance observer is developed to deal with the impact induced by the strange disturbance. Then, a new distributed adaptive synchronization criterion is put forward based on the approximation capability of the neural networks. Next, we propose the necessary and sufficient condition on the directed graph to ensure the synchronization error of all followers can be reduced small enough. Then, the distributed adaptive synchronization criterion is further explored because it is difficult to obtain the relative velocity measurements of the agents. The distributed adaptive synchronization criterion without the velocity measurement feedback is also designed to fulfill the current investigation. Finally, the simulation example is performed to verify the correctness and effectiveness of the proposed theoretical results.

Distributed Adaptive Cluster Synchronization for Linearly Coupled Nonidentical Dynamical Systems

This brief studies the cluster synchronization problem for networks of linearly coupled systems where the dynamical system models in different clusters are nonidentical. To ensure scalability and reconfigurability of networks, a distributed adaptive law is proposed to update the intra-cluster coupling strengths. Concretely, each system is required to update its own coupling strength with its cluster members, instead of using a common strength for all systems. The adaptive updating law applied by each system depends on relative states with respective to connected cluster members which are locally available information. Moreover, the parameters involved in the adaptive law of each system allow decentralized off-line computations. Both generic linear systems which are partial-state coupled and nonlinear oscillators which are full-state coupled are considered, respectively.

Finite-time adaptive synchronization of coupled uncertain neural networks via intermittent control

This paper considers the finite-time synchronization (FTS) of coupled neural networks (CNNs) with parameter uncertainties. Based on the adaptive periodically intermittent control method and the finite-time stability theory, some sufficient conditions are derived to achieve synchronization within a finite time. Both the models of CNNs with/without delays are considered and the corresponding upper-bounds of synchronization time are estimated as well. Finally, two illustrative examples are presented to demonstrate the effectiveness and applicability of the theoretical results.

A New 4D Hyperchaotic System with Dynamics Analysis, Synchronization, and Application to Image Encryption

In this paper, a new 4D hyperchaotic nonlinear dynamical system with two positive Lyapunov exponents is presented. Exhaustive dynamic analyses of the novel hyperchaotic model using several dynamical studies are described. The dynamics of the system considered are first investigated analytically and numerically to explore phenomena and the selection of hyperchaotic behavior utilized for designing image cryptosystem. Since the proposed hyperchaotic model has rich dynamics, it displays hidden attractors. It emerges from this dynamic the existence of a single unstable equilibrium point giving rise to self-excited attractors, hysteresis phenomenon, and hyperchaotic behavior strongly recommended for securing information by its character. Furthermore, the feasibility and synchronization of the proposed system are also presented by developing, respectively, Raspberry surveys and an adaptive synchronization approach of two identical hyperchaotic systems. By employing the hyperchaotic behavior of the 4D map, an image encryption scheme is proposed as well. It is one round of a pixel-based permutation and a bit-wise diffusion phase. The secret key of the 4D map is derived from the SHA-256 value of the input image. It acts as the signature of the input image. Hence, the secret key exhibits high sensitivity to single-bit alteration in the image, which makes the cryptosystem robust against chosen/known-plaintext attacks. Performance analyses prove that the proposed cryptosystem provides the best in terms of the performance/complexity trade-off, as compared to some recently published algorithms.

Distributed Adaptive Attitude Synchronization of Multiple Spacecraft With Event-Triggered Communication

This article investigates the distributed adaptive attitude synchronization problem for multiple rigid spacecraft with unknown inertial matrices and event-triggered communication. Under a directed topology condition, two distributed event-based adaptive attitude synchronization schemes are proposed. By introducing a reference system for each spacecraft, a distributed adaptive control algorithm is first developed, based on which a group of rigid spacecraft can be synchronized at a common attitude with zero angular velocity. Then, the case without angular velocity measurements is considered. By redesigning the reference system and resorting to a pseudovelocity filter, an event-based adaptive output feedback attitude synchronization algorithm is presented. It is shown that with the proposed control schemes, all the closed-loop signals are uniformly bounded and the attitude synchronization can be achieved, while Zeno behavior in each spacecraft can be excluded. Simulation results are provided to illustrate the effectiveness of the proposed control schemes.

Observer-Based Adaptive Synchronization Control of Unknown Discrete-Time Nonlinear Heterogeneous Systems.

This article is concerned with the optimal synchronization problem for discrete-time nonlinear heterogeneous multiagent systems (MASs) with an active leader. To overcome the difficulty in the derivation of the optimal control protocols for these systems, we develop an observer-based adaptive synchronization control approach, including the designs of a distributed observer and a distributed model reference adaptive controller with no prior knowledge of all agents' dynamics. To begin with, for the purpose of estimating the state of a nonlinear active leader for each follower, an adaptive neural network distributed observer is designed. Such an observer serves as a reference model in the distributed model reference adaptive control (MRAC). Then, a reinforcement learning-based distributed MRAC algorithm is presented to make every follower track its corresponding reference model on behavior in real time. In this algorithm, a distributed actor-critic network is employed to approximate the optimal distributed control protocols and the cost function. Through convergence analysis, the overall observer estimation error, the model reference tracking error, and the weight estimation errors are proved to be uniformly ultimately bounded. The developed approach further achieves the synchronization by means of synthesizing these results. The effectiveness of the developed approach is verified through a numerical example.

Adaptive Dual Synchronization of Fractional-Order Chaotic System with Uncertain Parameters

The problem of the dual synchronization of two different fractional-order chaotic systems with uncertain parameters is studied. This paper introduces a synchronization method in accordance with Lyapunov stability theory, and the adaptive controllers and adaptive laws are designed to realize the dual synchronization of fractional order chaotic systems. Finally, two numerical examples of unknown different fractional-order chaotic systems are also given to prove the accuracy of the theory in the paper, and the effectiveness and performance of the proposed adaptive dual synchronization strategy are verified by simulation.

High-Precision SLAM Based on the Tight Coupling of Dual Lidar Inertial Odometry for Multi-Scene Applications

Simultaneous Localization and Mapping (SLAM) is an essential feature in many applications of mobile vehicles. To solve the problem of poor positioning accuracy, single use of mapping scene, and unclear structural characteristics in indoor and outdoor SLAM, a new framework of tight coupling of dual lidar inertial odometry is proposed in this paper. Firstly, through external calibration and an adaptive timestamp synchronization algorithm, the horizontal and vertical lidar data are fused, which compensates for the narrow vertical field of view (FOV) of the lidar and makes the characteristics of vertical direction more complete in the mapping process. Secondly, the dual lidar data is tightly coupled with an Inertial Measurement Unit (IMU) to eliminate the motion distortion of the dual lidar odometry. Then, the value of the lidar odometry after correcting distortion and the pre-integrated value of IMU are used as constraints to establish a non-linear least-squares objective function. Joint optimization is then performed to obtain the best value of the IMU state values, which will be used to predict the state of IMU at the next time step. Finally, experimental results are presented to verify the effectiveness of the proposed method.

Adaptive synchronization with disturbance rejection for under-actuated ships with disturbances under thruster saturation

An adaptive synchronization control scheme with the disturbance estimation and rejection is proposed for the under-actuated ships with unknown time-varying disturbances under thruster saturation effects without leader ship’s velocities. The unknown time-varying disturbances are described as the sinusoidal disturbances whose amplitudes, frequencies and phases are uncertain. The disturbances are expressed by using an unknown parametric exogenous system which is converted into a canonical model with the disturbances as inputs. A disturbance filter is constructed to estimate the state vector in the canonical model such that the disturbances are represented by the parametric equations with exponentially decaying errors. The main highlights lie in that the anti-disturbance problem is transformed into the adaptive control problem based on parametric disturbance representations. This enables that the additional control filters are constructed to generate the filtered signals of the control deviations to on-line correct feedback control errors such that the adaptive disturbance rejection control would be workable under thruster saturation effects. The proposed adaptive synchronization scheme achieves the disturbance rejection and the thruster saturation attenuation simultaneously. Simulations with comparisons demonstrate the effectiveness and the superiority of the control scheme.

Distributed adaptive specified-time synchronization tracking of multiple 6-DOF fixed-wing UAVs with guaranteed performances

Different from the finite/fixed-time control methodologies on longitudinal/attitude synchronization or 2-D motion of UAVs, this article attempts to propose a distributed adaptive specified-time control scheme for synchronization tracking of networked 6-degree-of-freedom (DOF) UAVs. To be specific, the novel specified-time performance functions (STPFs) are designed in such a way that the desired performance bounds can be imposed on velocity and attitude tracking errors. Based on the transformed errors, by utilizing the barrier Lyapunov functions (BLFs), a distributed specified-time control scheme is constructed with adaptive robustifying terms to enhance the fault-tolerant ability and compensate the modeling uncertainties. By means of Lyapunov stability theory, it is proved that the resulting control scheme can guarantee the boundedness of all closed-loop state variables, and preserve the guaranteed performance bounds for synchronization tracking errors of velocity and attitude at the same time. Theoretical results are confirmed by experiment and simulation validations.

A Three‐Dimensional Autonomous System with a Parabolic Equilibrium: Dynamical Analysis, Adaptive Synchronization via Relay Coupling, and Applications to Steganography and Chaos Encryption

This paper is reporting on electronic implementation of a three‐dimensional autonomous system with infinite equilibrium point belonging to a parabola. Performance analysis of an adaptive synchronization via relay coupling and a hybrid steganography chaos encryption application are provided. Besides striking parabolic equilibrium, the proposed three‐dimensional autonomous system also exhibits hidden chaotic oscillations as well as hidden chaotic bursting oscillations. Electronic implementation of the hidden chaotic behaviors is done to confirm their physical existence. A good qualitative agreement is shown between numerical simulations and OrCAD‐PSpice results. Moreover, adaptive synchronization via relay coupling of three three‐dimensional autonomous systems with a parabolic equilibrium is analysed by using time histories. Numerical results demonstrate that global synchronization is achieved between the three units. Finally, chaotic behavior found is exploited to provide a suitable text encryption scheme by hidden secret message inside an image using steganography and chaos encryption.

Fixed-Time Adaptive Time-Varying Matrix Projective Synchronization of Time-Delayed Chaotic Systems with Different Dimensions

This paper deals with the fixed-time adaptive time-varying matrix projective synchronization (ATVMPS) of different dimensional chaotic systems (DDCSs) with time delays and unknown parameters. Firstly, to estimate the unknown parameters, adaptive parameter updated laws are designed. Secondly, to realize the fixed-time ATVMPS of the time-delayed DDCSs, an adaptive delay-unrelated controller is designed, where time delays of chaotic systems are known or unknown. Thirdly, some simple fixed-time ATVMPS criteria are deduced, and the rigorous proof is provided by employing the inequality technique and Lyapunov theory. Furthermore, the settling time of fixed-time synchronization (Fix-TS) is obtained, which depends only on controller parameters and system parameters and is independent of the system’s initial states. Finally, simulation examples are presented to validate the theoretical analysis.

Signal Transmission by Sampled-time Adaptive Synchronization of Time-varying Chaotic Systems

In the paper, the adaptive synchronization problem is studied for a class of time-varying nonlinear systems. The only assumption imposed is the boundedness of the rate of change of the controlled system parameters, while the initial uncertainty can be quite large. The adaptation algorithms in the discrete-time form are derived based on adaptive control of nonlinear time-varying systems with an explicit reference model. As the result, the estimate of the limiting deviation of the solution of the closed-loop system from that of the reference model was obtained. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limiting error in the system can be made arbitrarily small despite a possibly big range of system parameter values. The systems based on a direct approach are considered. The procedure for the synthesis of a sampled-time adaptive controller and analysis of the synthesized system is illustrated by an example of the signal transmission system. The results obtained allow one to build and analyze a wide class of adaptive systems with reference models under time-varying conditions.

Event-Triggered Adaptive Fault-Tolerant Synchronization Tracking Control for Multiple 6-DOF Fixed-Wing UAVs

In contrast with most existing results concerning unmanned aerial vehicles (UAVs) wherein two-degree or only attitude/longitudinal dynamics are considered, this article proposes an event-triggered cooperative synchronization fault-tolerant control (FTC) methodology for multiple fixed-wing UAVs whose dynamics are six-degree-of-freedom (DOF) with twelf-state-variables subject to actuator faults, modeling uncertainties, and external disturbances. More precisely, an event-triggering mechanism is devised to determine the time instants of updating control signals, which reduces the signal transmission burden, while saving on system resources. The Zeno phenomenon is excluded in the sense of guaranteeing that the time between two consecutive switchings is lower bounded by a positive constant. The actuator faults as well as the network induced errors are handled via the bound estimation approach and some well-defined smooth functions. By strict Lyapunov arguments, all closed-loop signals are proved to be semi-globally uniformly ultimately bounded (SGUUB) and the synchronization tracking errors of speed and attitude converge to a residual set around origin whose size can be made arbitrarily small through selecting appropriate design parameters.

Алгоритм адаптивной синхронизации системы многоканального рулевого привода

The article presents the construction of an adaptive control algorithm that synchronizes the position and equalizes the loading forces of a hybrid drive system. The system consists of one electro-hydraulic actuator (EHA) and one electro-mechanical actuator (EMA) and operates in active-active mode. Destination algorithm to meet the growing requirements for the reliability of civil aircraft steering gears. A mathematical model of the system is presented, which includes non-linear friction forces in the engine and actuator, as well as non-linear flowdifferential characteristics of the hydraulic distribution valve. The synthesis of an adaptive position and force synchronization controller for two channels is given, taking into account nonlinear factors. The results of the research when comparing the efficiency of the algorithm were performed in the MatLab/Simulink environment.

Adaptive Synchronization of Fractional-Order Complex-Valued Neural Networks With Time-Varying Delays

In this paper, the adaptive synchronization of fractional-order complex-valued neural networks with time-varying delays(FOCVNNTDs) is investigated. First, two novel fractional-order differential inequalities with time delays are established, which can be seen as an extension of Halanay inequality. Besides, complete synchronization and quasi-projective synchronization of FOCVNNTDs are investigated based on the two novel inequalities using a novel adaptive controller. In addition, instead of separating the complex-valued neural networks into two real-valued networks, a non-decomposition method is adopted to study the adaptive synchronization of FOCVNNTDs, which avoids the difficulty and complexity of theoretical analysis. Finally, some numerical simulation examples are provided to demonstrate the validity of our theory.

Fast synchronization of symmetric Hénon maps using adaptive symmetry control

The article discusses the possibility of synchronizing adaptive discrete chaotic maps through the control of the symmetry coefficient. Since a change in the symmetry coefficient in symmetric chaotic maps possesses a much less influence on the system oscillation mode than a change in nonlinearity parameters, we assume that the synchronization of such systems can be achieved in a small number of iterations. To experimentally examine this hypothesis, we studied three cases of adaptive synchronization feedback controllers for the conventional Hénon map and adaptive Hénon map. We found that synchronization occurs faster while the symmetry coefficient is controlled by comparing the synchronization times in all considered cases. Averagely, an accurate estimate of the adaptive coefficient is achieved after 3–5 iterations. Applying this approach to the communication systems based on modulation through switching parameters of chaotic systems can significantly reduce the transient processes inherent in this method. The numerical experiments show that it is possible to decrease the transmission time by more than 25%, even in the case of short messages.

An investigation on microscopic chaos controlling of identical chemical reactor system via adaptive controlled hybrid projective synchronization

An investigation on microscopic chaos controlling of identical chemical reactor system via adaptive controlled hybrid projective synchronization

Pinning synchronization and adaptive synchronization of complex-valued inertial neural networks with time-varying delays in fixed-time interval

This article concentrates on pinning synchronization and adaptive synchronization problems of complex-valued inertial neural networks with time-varying delays in fixed-time interval. First, regarding complex-valued inertial neural networks model as an entirety instead of reducing this system to first-order differential equation, separating the real and imaginary parts of this system into an equivalent real-valued one, and establishing a novel Lyapunov function, the fixed-time stability for the closed-loop error system is guaranteed via partial nodes controlled directly by a new pinning controller which involves the state derivatives and other proper terms. Then, from the point of saving cost and avoiding resources waste, a new pinning adaptive controller is further developed and sufficient condition ensuring the adaptive fixed-time stability for the closed-loop error system is also derived. In the end, the effectiveness of these results is verified by a numerical example.