Fixed-time Synchronization Control Research Articles

Fixed-time synchronization control of fuzzy inertial neural networks with mismatched parameters and structures

Fixed-time synchronization control of fuzzy inertial neural networks with mismatched parameters and structures

Event-based fixed-time synchronization of neural networks under DoS attack and its applications

In this paper, the fixed-time synchronization control for neural networks with discontinuous data communication is investigated. Due to the transmission blocking caused by DoS attack, it is intractable to establish a monotonically decreasing Lyapunov function like the conventional analysis of fixed-time stability. Therefore, by virtue of recursive and reduction to absurdity approaches, novel fixed-time stability criteria where the estimated upper bound of settling-time is inherently different from existing results are presented. Then, based on the developed conditions, an event-triggered control scheme that can avoid Zeno behavior is designed to achieve synchronization of master–slave neural networks under DoS attack within a prescribed time. For comparison, the established control scheme is further discussed under the case without DoS attack, and the circumstance that there is no attack or event-triggered mechanism, respectively. Simulation results are finally provided to illustrate the significant and validity of our theoretical research. Especially, in terms of encryption and decryption keys generated from the synchronization behavior of chaotic networks, we specifically discuss the application of the proposed fixed-time synchronization scheme to image and audio encryption.

Continuous fixed-time synchronization control for uncertain industrial master-slave robotics system with improved transparency

Industrial telerobotics system (ITS) enables robots to implement remote, dangerous, and complicated manufacturing tasks by incorporating human intelligence. Higher requirements are put forward for the working speed and performance of ITS. However, for ITS, only asymptotic convergence can be realized by existing control strategies, which have poor robust performance. In view of these theoretical and practical problems, this article addresses fixed-time synchronization control issue for a class of ITS with unknown parametric/nonparametric uncertainties and external disturbances. Satisfactory force and position performance can be achieved with the designed novel control algorithms. Firstly, based on the impedance control frame, two reference models are constructed for the master and slave robots by considering force and position signals transmission between master and slave, respectively. Then, a new adaptive sliding mode disturbance observer (ASMDO) is developed to realize the estimation of external disturbances and system uncertainties in higher speed and higher precision under relaxed assumption. Moreover, a novel continuous fixed-time control (CFTC) scheme is developed to guarantee good position and force synchronization performances, simultaneously. Finally, the effectiveness of the suggested control method is validated with simulations and experimental results.

Fixed-time synchronization for inertial Cohen–Grossberg delayed neural networks: An event-triggered approach

This paper addresses the fixed-time synchronization problem for inertial Cohen–Grossberg neural networks with external disturbances and time-varying delays. Compared with some existing works about fixed-time synchronization control methods, a novel controller is constructed with a dynamic exponential term, which can contain the two exponents. Moreover, taking into account the increase of network complexity as well as a huge quantity of data transmission, an event-triggered mechanism is introduced to effectively utilize the limited network bandwidth. By employing the variable transformation method, differential mean value theorem, and the fixed-time stability theory, some sufficient conditions ensuring the fixed-time synchronization of inertial Cohen–Grossberg neural networks are established. Finally, two numerical examples are given to illustrate the validity of the obtained results.

Fixed-Time Synchronization Analysis of Genetic Regulatory Network Model with Time-Delay

The synchronous genetic regulatory networks model includes the drive system and response system, and the drive-response system is symmetric. From a biological point of view, this model illustrates the dynamic behaviors in gene-to-protein processes, in terms of transcription and translation. This paper introduces a model of genetic regulatory networks with time delay. The fixed-time synchronization control problem of the proposed model is studied based on fixed-time stability theory and the Lyapunov method. Concretely, the authors first propose a way to switch from the given model to matrix form. Then, two types of novel controllers are designed and the corresponding sufficient conditions are investigated respectively to ensure the fixed-time synchronization goal. Moreover, the settling times of fixed-time synchronization are estimated for the addressed discontinuous controllers, which are not dependent on the initial or delayed states of the model. Finally, numerical simulations are presented and compared to illustrate the benefits of the theoretical results.

Chaos synchronization control for stochastic nonlinear systems of interior PMSMs based on fixed-time stability theorem

This paper proposes an enhanced chaos synchronization control scheme of stochastic nonlinear systems for the permanent magnet synchronous motors(PMSMs) applications for dynamic operating mechanism under different working environment. Firstly, a novel fixed-time stochastic stability theorem and convergence for the stochastic nonlinear system is valid through formulating a novel Lyapunov function. Different from what has been achieved on the fixed-time stability, it’s not the usual range but it’s more precise for settling time which improving control performance effectually. Secondly, the chaos synchronization issue of driven-response PMSMs with stochastic noise is firstly investigated based on the proposed Lyapunov theorem synchronizing the complex dynamic systems considering practical significance. Finally, the fixed-time synchronization control scheme is developed via applying the adaptive algorithms, furthermore, through constructing a reasonable synchronization dynamic error system achieving stability in probability of fixed time. A simulation analysis is demonstrated to verify the availability of the proposed control strategy.

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.

Fast fixed-time synchronization control analysis for a class of coupled delayed Cohen-Grossberg neural networks

In a fixed-time control system, the convergence rate and the fixed settling time are two important performance indexes. In this paper, a novel fixed-time control law is proposed and designed to control a class of coupled delayed Cohen-Grossberg neural networks to achieve synchronization with fast convergence rate within a fixed settling time. It should be emphasized that the derived settling time approach can provide a tighter settling time to more effectively reflect the performance for fast convergence rate of the considered controlled system. Moreover, to show the advantages of the proposed fixed-time control law and the derived fixed settling time approach, the existing related control laws and fixed settling time approaches are further discussed. In addition, the obtained fixed-time synchronization control theory is applied to a secure communication scenario, which further shows the feasibility and innovation of the addressed theoretical results.

Fixed-Time Synchronization Control of Delayed Dynamical Complex Networks.

Fixed-time synchronization problem for delayed dynamical complex networks is explored in this paper. Compared with some correspondingly existed results, a few new results are obtained to guarantee fixed-time synchronization of delayed dynamical networks model. Moreover, by designing adaptive controller and discontinuous feedback controller, fixed-time synchronization can be realized through regulating the main control parameter. Additionally, a new theorem for fixed-time synchronization is used to reduce the conservatism of the existing work in terms of conditions and the estimate of synchronization time. In particular, we obtain some fixed-time synchronization criteria for a type of coupled delayed neural networks. Finally, the analysis and comparison of the proposed controllers are given to demonstrate the validness of the derived results from one numerical example.

A Novel Fast Fixed-Time Control Strategy and Its Application to Fixed-Time Synchronization Control of Delayed Neural Networks

A Novel Fast Fixed-Time Control Strategy and Its Application to Fixed-Time Synchronization Control of Delayed Neural Networks

A novel fixed-time stability strategy and its application to fixed-time synchronization control of semi-Markov jump delayed neural networks

This paper emphasizes on a novel fixed-time stability strategy and its application to fixed-time synchronization control for a class of semi-Markov jump delayed Cohen-Grossberg neural networks (SMJDCGNNs). First, a novel fixed-time stability strategy for a class of nonlinear delayed systems is proposed, which is a generalization of the existing stability strategies. Second, the addressed fixed-time stability strategy is applied to solving fixed-time synchronization control for a class of SMJDCGNNs, whose framework generalizes the existing Cohen-Grossberg neural networks (CGNNs). The application testifies that compared with the existing fixed-time stability strategies, the obtained fixed-time stability strategy can provide a tighter settling time which can more effectively and accurately estimate the convergence time of the studied delayed system. Finally, we give a comparative example to illustrate the validity of our results.

New study on fixed-time synchronization control of delayed inertial memristive neural networks

The problem of fixed-time synchronization (FTS) control for memristive neural networks (MNNs) with discrete timedelay and inertia term is investigated in this work. Firstly, delayed inertial memristive neural networks (DIMNNs) are characterized as the differential equations, which is second-order and has discontinuous right-hand side. Secondly, a suitable two-parameter variable substitution method is advocated for the second-order derivatives of states, and then DIMNNs can be represented in the shape of first-order differential equation. Thirdly, a new fixed-time criterion and FTS of DIMNNs are achieved under the designed feedback controller in the light of comparison lemma and inequality techniques. Meanwhile, the settling-time (ST) of FTS is estimated, it could be adjusted to arbitrary expected values by controller parameters without relying on the initial conditions and also fully reflects that a tighter ST value is obtained. Finally, the effectiveness of the brought forward theoretical results is testified via a numerical simulation.

Finite-time and fixed-time synchronization control of discontinuous fuzzy Cohen-Grossberg neural networks with uncertain external perturbations and mixed time delays

This paper aims to investigate the synchronization control of a class of discontinuous fuzzy Cohen-Grossberg neural networks (DFCGNNs) with uncertain external perturbations and mixed time delays (discrete and distributed time-delays). By using functional differential inclusions theory, inequality technique and the non-smooth analysis of Lyapunov-Krasovskii functional, a simple switching adaptive control is designed and some new criteria are obtained to achieve the finite-time synchronization of the proposed drive-response systems. Besides, the upper bound of the settling time is estimated. Based on the finite-time synchronization, we further present a novel discontinuous state-feedback controller to the response neural system in order to derive the fixed-time synchronization criteria and estimate the settling time. Compared with the previous results which can only fixed-timely synchronize or finite-timely synchronize some simple delayed fuzzy neural network systems with continuous activation functions and without uncertain external perturbations, the DFCGNNs with uncertain external perturbations and mixed time delays addressed and the theoretical results of this paper are more generalized and inclusive. Finally, several simulation examples and remarks are provided to verify the correctness and advantages of the main results.

Fixed Time Synchronization Control for Bilateral Teleoperation Mobile Manipulator With Nonholonomic Constraint and Time Delay

In this brief, the fixed time synchronization control is investigated for nonholonomic mobile manipulator teleoperation system. The mobile manipulator is divided into two subsystems for analysis, which are nonholonomic mobile platform and holonomic constrained manipulator. Coupling terms between two subsystems are considered as disturbances. A fixed time synchronization controller is proposed to deal with the parameter uncertainties and unknown bounded disturbances. Lyapunov stability theory guarantees the stability of the closed-loop teleoperation system. Numerical simulations verify the effectiveness of the proposed results.

Fixed-time synchronization of fractional order memristive MAM neural networks by sliding mode control

In this paper, we first established the fractional order memristive multidirectional associative memory neural networks (FMMAMNNs) model, and then considered its fixed-time synchronization control problem. On the basis of sliding model control and Lyapunov stability theorem, a fractional order sliding mode controller is constructed. By adding this controller to the response system, the error of the driver-response systems gradually converges to 0 in a fixed time. Compared with the previous researches, this paper considers a more complex model, and the proposed control theories can ensure that the setting time is only related to the model and controller, but not to the initial states of the system. Besides, the control theories are also applicable to the integer order models. Finally, two numerical simulations are given, the results show the validity of the theories.

Fixed-time synchronization control for a class of nonlinear coupled Cohen–Grossberg neural networks from synchronization dynamics viewpoint

This paper is mainly concerned with fixed-time synchronization control for a class of Cohen–Grossberg neural networks (CGNNs) with nonlinear coupling and time-varying delay based on synchronization dynamics. First, by using a derived sufficient condition of fixed-time synchronization (FTS) for nonlinear coupled CGNNs (NCCGNNs) with time-varying delay, a novel fixed-time synchronization controller with time-varying delay is designed. Second, by combining the synchronization dynamic viewpoint and the obtained fixed-time synchronization control rule, several useful fixed-time synchronization controllers (FTSCs) are derived. Third, comparisons with known conclusions are provided to show the innovation and feasibility of the proposed fixed-time synchronization control methods. Finally, two examples are given to verify the effectiveness of the theoretical results. Compared with related works, the advantages of this paper are as follows: (1) The designed novel FTSCs can scientifically and efficiently process the time-varying delay of the addressed coupled CGNNs; (2) The derived settling time of the FTS built on FTSCs can reflect the effect of the proposed system’s parameters on the synchronization convergence time.

Finite-time and fixed-time synchronization control of fuzzy Cohen-Grossberg neural networks

This paper aims to investigate the finite-time and fixed-time robust synchronization of fuzzy Cohen-Grossberg neural networks with discontinuous activations. To deal with the discontinuous property, the framework of Filippov solution is invoked to solve the inexistence of the classical solutions. For the purpose of achieving fixed-time synchronization, we turn to investigating the fixed-time stability problem of the error system between the drive-response systems. By the functional differential inclusions theory, inequality technique and the non-smooth Lyapunov-Krasovskii functional and designing a simple discontinuous state-feedback control law for the response neural system, some sufficient algebraic criteria are derived to achieve synchronization within a fixed time, and the settling time is given. Moreover, based on the fixed-time robust synchronization and under the same basic assumptions, we further complete the finite-time synchronization of the addressed drive-response systems by designing a simple switching adaptive controller, and the upper bound of the settling time is also estimated. It should be regarded as the first time to study the finite-time synchronization of fuzzy Cohen-Grossberg neural networks with discontinuous activations based on the adaptive control. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed synchronization strategies.

Design of fixed-time synchronization algorithm with applications

Fixed-time synchronization problem for a class of leader–follower multi-agent systems with second-order nonlinearity is studied in this article. A new fixed-time synchronization control algorithm is developed by effectively combining homogeneous system theory, Lyapunov stability theory, and fixed-time/finite-time control technology. The leader–follower multi-agent system is considered to achieve fixed-time synchronization control. Finally, numerical simulations including coordination control multiple pendulum robot systems and electric power networks are carried out to verify the control performance of the control strategy.

Fixed-Time Synchronization Control for a Class of Master–Slave Systems Based on Homogeneous Method

This brief investigates the fixed-time synchronization problem for a class of master–slave systems with second-order nonlinear dynamics via output feedback. Based on the homogeneous system theory, a new fixed-time synchronization control algorithm and a fixed-time observer are designed such that the synchronization of master–slave coupling systems can be achieved in a fixed time. It is theoretically shown that the synchronization time can be pre-determined which is independent of any initial conditions. Numerical simulations on synchronization of master–slave nonlinear forced pendulum systems are finally performed to illustrate the effectiveness of the proposed method.

Fixed-time synchronization control of memristive MAM neural networks with mixed delays and application in chaotic secure communication

Abstract In this paper, the fixed-time synchronization control problem of memristive multidirectional associative memory neural networks (MMAMNNs) is considered. Based on the nonlinear and chaos characteristics of memristor, a chaotic model is constructed. And then, utilizing the Lyapunov stability theory, two appropriate controllers are constructed and different activation functions are used. This control method ensures that drive system and response system can achieve synchronization within a fixed time. So, compared with previous studies, it has more practical value. In addition, we present a fixed-time synchronization chaotic encryption method, the chaos characteristic of the model is used to encrypt plaintext, and the decryption of ciphertext is realized based on the synchronization control theories. Finally, several numerical simulations are given to demonstrate the validity of the theories and the chaotic secure communication scheme.