Robust Adaptive Synchronization Research Articles

Neural Network-based Robust Adaptive Synchronization and Tracking Control for Multi-Motor Driving Servo Systems

Neural Network-based Robust Adaptive Synchronization and Tracking Control for Multi-Motor Driving Servo Systems

Synchronization of chaotic satellite systems with an unknown parameter

Spacecraft (satellite) formation has several applications in space exploration. Synchronization controllers are essential in satellite formation systems. This article proposes a novel robust adaptive synchronization control (RASC) technique for two identical three-dimensional chaotic satellite systems attitude synchronization with an unknown system parameter, unknown bounded model uncertainties, unknown external disturbances, and nonlinear terms. This controller achieves smooth error vector convergence to zero. The closed-loop has a robust performance as the controller avoids plant nonlinear terms cancellation. This controller has two parts. (i) A nonlinear controller for keeping the closed-loop stable; it flourishes robust and faster error vector convergence to zero with reduced fluctuations. (ii) An adaptive nonlinear controller that compensates exogenous disturbances and model uncertainties using online estimations of model uncertainties and bounds. The Lyapunov stability theory assures the closed-loop's global asymptotic robust stability. Computer simulation results-based analysis verifies the theoretical findings. The article includes a comparative study and discusses the control effort saturation effects.

RBF Neural Network-Based Adaptive Robust Synchronization Control of Dual Drive Gantry Stage With Rotational Coupling Dynamics

As a typical mechatronics system, dual drive gantry stage has been widely used in high-end intelligent equipment. In this paper, an adaptive robust synchronization control scheme based on RBF neural network is presented to improve the synchronization accuracy and robust performance of dual drive gantry system. In order to overcome the limitation of system performance caused by ignoring high-frequency rotation mode in traditional modeling, a more reasonable rotational dynamic coupling model of gantry table was established. In addition, the adaptive robust control method with expected compensation is adopted to avoid the interference of measurement noise in the system and realize accurate compensation of the model. The advantages of RBF neural network infinite approximation are used to deal with the effects of model compensation residual, unmodeled dynamics and uncertain disturbances. The stability of the closed-loop system is proved by the Lyapunov theorem. Finally, different control strategies are used to conduct comparative experiments and the experimental results verify the superiority and effectiveness of the proposed control strategy. Note to Practitioners—The synchronization problem of dual drive gantry stage is a research hotspot in the industrial field and its control accuracy and robustness are important indexes that affect the system performance. In this paper, the coupled dynamics model of the gantry system is analyzed and established. In addition, an adaptive robust synchronous control strategy based on RBF neural network is presented to deal with various nonlinearities, mechanical strong coupling constraints and external unknown disturbances in the system, which improves the synchronization accuracy and anti-interference ability of the system. In practical industrial application, the designed controller can be applied to a class of dual-drive gantry systems to ensure the quality of product processing. At the same time, under the strong disturbance of complex working conditions, machine damage or more serious safety accidents caused by asynchronous movement can be avoided and the system reliability can be effectively improved, which is of great significance to industrial production.

Function Projective Synchronization of Two Complex Networks with Unknown Sector Nonlinear Input and Multiple Time-Varying Delay Couplings

This paper deals with the function projective synchronization of two complex dynamic networks with unknown sector nonlinear input, multiple time-varying delay couplings, model uncertainty, and external interferences. Based on Lyapunov stability theory and inequality transformation method, the robust adaptive synchronization controller is designed, by which the drive and response systems can achieve synchronization according to the function scaling factor. Different from some existing studies on nonlinear system with sector nonlinear input, this paper studies the synchronization of two complex dynamic networks when the boundary of sector nonlinear input is unknown. The controller does not include the boundary value of the sector nonlinear input and the time delay term, so it is more practical and relatively easy to implement. The corresponding simulation examples demonstrate the effectiveness of the proposed scheme.

Robust Multi-Mode Synchronization of Chaotic Fractional Order Systems in the Presence of Disturbance, Time Delay and Uncertainty with Application in Secure Communications

This paper investigates the robust adaptive synchronization of multi-mode fractional-order chaotic systems (MMFOCS). To that end, synchronization was performed with unknown parameters, unknown time delays, the presence of disturbance, and uncertainty with the unknown boundary. The convergence of the synchronization error to zero was guaranteed using the Lyapunov function. Additionally, the control rules were extracted as explicit continuous functions. An image encryption approach was proposed based on maps with time-dependent coding for secure communication. The simulations indicated the effectiveness of the proposed design regarding the suitability of the parameters, the convergence of errors, and robustness. Subsequently, the presented method was applied to fractional-order Chen systems and was encrypted using the chaotic masking of different benchmark images. The results indicated the desirable performance of the proposed method in encrypting the benchmark images.

Output feedback synchronization control for supply vessels during underway replenishment with unknown dynamics and disturbances under input saturation

ABSTRACT This paper investigates the synchronization control problem for a supply vessel during underway replenishment with unknown dynamics, unknown disturbances, input saturation and unavailable velocities. A virtual trajectory shifted by a distance at an angle relative to the trajectory of the supplied vessel is planned. A high-gain observer observer is employed to estimate unavailable vessel velocities and an auxiliary design system is constructed to address the effect of input saturation. Then, the adaptive radial basis function neural networks are employed to approximate unknown dynamics and the adaptive laws are derived to estimate bounds of unknown disturbances. Incorporating the above into the dynamic surface control method, an output feedback robust adaptive neural synchronization control law is developed to force the supply vessel to track the virtual trajectory such that the synchronization navigation between the supply and the supplied vessels is realized. The theoretical analysis and simulation results validate our developed control scheme.

Robust observer-based adaptive synchronization control of uncertain nonlinear bilateral teleoperation systems under time-varying delay

Due to the practical restrictions such as uncertain dynamics, external disturbances and time-varying delays and lack of enough information about the remote environment, the performance of teleoperation systems cannot be guaranteed in most cases. However, some practical tasks such as tele-surgery conducted by the nonlinear teleoperation system require high performance. Recent research on teleoperation systems motivates us to propose a new robust adaptive control law for nonlinear bilateral teleoperation systems with time-varying delays, external disturbances and uncertain dynamics in a unified framework. To this end, a novel adaptive torque observer is developed to relax the system from force sensors. The main advantage of this paper is to design properly a mechanism, which is free from joint accelerations due to the acceleration measurement difficulty in robotic systems. Moreover, the key point of the proposed algorithm is to enhance the robust behavior of the system in the presence of various uncertainties by adding an auxiliary term in the control loop. Furthermore, the stability and the convergence of synchronization error to zero are also proven with the aid of both Lyapunov-Krasovskii function and linear matrix inequality. Simulation results emphasize on the effectiveness of the proposed Observed-based control approach in comparison with the related research.

Fixed-Time Adaptive Robust Synchronization with a State Observer of Chaotic Support Structures for Offshore Wind Turbines

The chaotic support structures for offshore wind turbines are often subjected to a severe environment. A robust control scheme needs to be considered to maintain them in a safe operational limit. Robust sliding mode control (SMC) scheme can provide an excellent robust controller against this severe and challenging environment for these chaotic structures. This paper proposes a novel fixed-time adaptive sliding mode control scheme with a state observer to synchronize chaotic support structures for offshore wind turbines in the presence of matched parametric uncertainties. The proposed controller is a new integration of adaptive control concept, SMC method, fixed-time stability concept and a state observer. A fixed-time stability concept is used to provide stability for the system within a presented time regardless of initial conditions. The adaptive concept is utilized to provide an online estimator of the uncertain upper bound. Also, a nonlinear observer is employed to provide an online estimator of an unmeasured state in the controller. Lyapunov stability theorem is used to analyze fixed-time stability of the system based on SMC methodology. The simulation results demonstrate that the proposed controller is able to ensure fixed-time synchronization along with providing precise means to estimate the unmeasured state as well as uncertainty upper bound.

Accurate physical modeling and synchronization control of dual-linear-motor-driven gantry with dynamic load

To achieve high-accuracy tracking of a dual-linear-motor-driven (DLMD) gantry, high-level synchronization between redundant actuators becomes a non-negligible factor and also a difficult issue to be solved priorly. Especially, when both X and Y axes are simultaneously operating to accomplish complex tasks efficiently, additional coupling effects will be generated by the dynamic load presented on the crossbeam, which makes the synchronization issue more complicated than the case with static load. However, due to the absence of an accurate model to fully reveal the complete coupling characteristics, existing approaches to this issue still have inherent limitations. Therefore, this paper focuses on the systematic physical modeling and synchronization control of a DLMD gantry with a dynamic load presented on the crossbeam. A complete coupling mathematical model is established first, by fully considering two linear motions (X-axis and Y-axis) and also including the additional rotational motion of the crossbeam. Built upon the effective model information, corresponding solutions by compensating the dynamic load effects and actively controlling the rotational dynamics to regulate the internal forces have been proposed, leading to a novel adaptive robust synchronization control method. The results of comparative experiments verify the effectiveness and superiority of the proposed method in dealing with the synchronization issue subjected to dynamic load effects.

Robust adaptive command-filtered backstepping synchronization navigation control with prescribed performance for supply ship during underway replenishment

In the presence of unknown environmental disturbances, this paper develops a robust adaptive synchronization navigation control design with prescribed performance for the supply ship during underway replenishment using the adaptive technique, the prescribed performance control (PPC) technique and the command-filtered backstepping approach. The adaptive law is derived to estimate the bounds of unknown environmental disturbances, the PPC technique is introduced to guarantee the prescribed transient and steady-state performance of synchronization control and the command filter is employed to avoid the direct analytic derivation of the virtual stabilizing function in the conventional backstepping design. The theoretical analysis proves that the designed control law can realize the synchronization navigation between the supply and the main ships with prescribed performance, while guaranteeing the uniform ultimate boundedness of all signals in the synchronization closed-loop control system of the supply ship. Simulation results on a supply ship demonstrate the effectiveness of the designed synchronization navigation control law and the robustness to unknown environmental disturbances.

Robust Adaptive Synchronization of a Class of Uncertain Chaotic Systems with Unknown Time-Delay

In this paper, a robust adaptive control strategy is proposed to synchronize a class of uncertain chaotic systems with unknown time delays. Using Lyapunov theory and Lipschitz conditions in chaotic systems, the necessary adaptation rules for estimating uncertain parameters and unknown time delays are determined. Based on the proposed adaptation rules, an adaptive controller is recommended for the robust synchronization of the aforementioned uncertain systems that prove the robust stability of the proposed control mechanism utilizing the Lyapunov theorem. Finally, to evaluate the proposed robust and adaptive control mechanism, the synchronization of two Jerk chaotic systems with finite non-linear uncertainty and external disturbances as well as unknown fixed and variable time delays are simulated. The simulation results confirm the ability of the proposed control mechanism in robust synchronization of the uncertain chaotic systems as well as to estimate uncertain and unknown parameters.

A New Robust Finite-Time Synchronization and Anti-Synchronization Method for Uncertain Chaotic Systems by Using Adaptive Estimator and Terminal Sliding Mode Approaches

In this paper, a new robust adaptive finite-time synchronization method has been proposed for chaotic systems by considering model uncertainties and external disturbances. The finite-time synchronization between master and slave systems is achieved under terminal sliding mode control method. The most important innovation of this paper is designing of an adaptive law to estimate the unknown upper bound of the disturbance and uncertainty. To handle the disturbances/uncertainties with unknown upper bounds and get finite-time synchronization, the adaptive law is combined with terminal sliding mode control method. Numerical simulation results and comparative studies show the effectiveness of proposed method.

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things.

Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.

A new fractional-order hyperchaotic memristor oscillator: Dynamic analysis, robust adaptive synchronization, and its application to voice encryption

Abstract The present study proposes a new fractional-order hyperchaotic memristor oscillator. The proposed system is studied through numerical simulations and analyses, such as the Lyapunov exponents, bifurcation diagrams, and phase portraits. Then, using the sliding mode concept, a robust adaptive control scheme is designed to synchronize the proposed system. The adaptation mechanism is implemented to estimate the unknown parameters of the slave system. Then, the output of the proposed adaptation mechanism is used for the control scheme. The stability of the closed-loop system is proven via a fractional version of the Lyapunov stability theorem and Barbalat's lemma. Numerical simulations of synchronization are shown to investigate the performance of the developed control technique on the uncertain fractional-order hyperchaotic memristor oscillator. Finally, as an engineering application, the proposed fractional-order system is implemented for voice encryption. In this regard, to show the appropriate performance of the proposed system for voice encryption, statistical characteristic of the encryption and decryption processes are performed through different methods including correlation, entropy, root mean square, and root sum of squares.

Oscillation free robust adaptive synchronization of chaotic systems with parametric uncertainties

The complexity of the closed-loop system, short transient response time, and fast synchronization error convergence rates are the three basic parameters that limit hacking in the data encryption and secure the communication systems. This paper addresses the following two challenges: The full-order synchronization (FOS) of two parametrically excited second-order nonlinear pendulum (PENP) chaotic systems with uncertain parameters. The reduced-order synchronization (ROS) between the canonical projection part of an uncertain third-order chaotic Rossler and the uncertain PENP systems. This article designs a new robust adaptive synchronization control (RASC) algorithm to address the above two challenges. The proposed controller achieves the FOS and ROS in a shorter transient time, and the synchronization error signals converge to the origin with faster rates in the presence of bounded unknown state-dependent and time-dependent disturbances. The Lyapunov direct method verifies this convergence behavior. The paper provides parameters updated laws that confirm the convergence of the uncertain parameters to some fixed values. The controller does not cancel the nonlinear terms of the plant; this property of the controller keeps the nonlinear terms in the closed-loop that results in the enhanced complexity of the dynamical system. The proposed RASC strategy is successful in synthesizing oscillation free convergence of the synchronization error signals to the origin for reducing the transient time and guarantees the asymptotic stability at the origin. The simulation results endorse the theoretical findings.

Robust adaptive synchronization of complex network with bounded disturbances

In this paper, we investigate distributed robust adaptive synchronization for complex networked systems with bounded disturbances. We propose both average synchronization protocol and leader-following synchronization protocol based on adaptive control and variable structure control strategies. The synchronization conditions do not require any global information except a connection assumption under the adaptive control method. Furthermore, the external disturbances are attenuated effectively. Finally, we present numerical simulations to illustrate the theoretical findings.

Stability analysis and robust synchronization of fractional‐order competitive neural networks with different time scales and impulsive perturbations

SummaryThis article mainly examine a class of robust synchronization, global stability criterion, and boundedness analysis for delayed fractional‐order competitive type‐neural networks with impulsive effects and different time scales. Firstly, by endowing the robust analysis skills and a new class of Lyapunov‐Krasovskii functional approach, the error dynamical system is furnished to be a robust adaptive synchronization in the voice of linear matrix inequality (LMI) technique. Secondly, by ignoring the uncertain parameter terms, the existence of equilibrium points are established by means of topological degree properties, and the solution representation of the considered network model are provided. Thirdly, a novel global asymptotic stability condition is proposed in the voice of LMIs, which is less conservative. Finally, our analytical results are justified with two numerical examples with simulations.

Robust Adaptive Attitude Synchronization of Uncertain Rigid Bodies on Special Orthogonal Group with Communication Delays and Gyro Biases

The paper proposes an attitude synchronization algorithm of rigid bodies on Special Orthogonal Group SO(3), with parameter uncertainties, external disturbances, gyro biases and communication delays. A set of two-order linear filters are introduced to cope with discontinuous communication delays, and only attitude information is required to be exchanged between rigid bodies. Then a set of gyro bias estimators are constructed with exponential convergence rates in the constant bias case and can also deal with time-varying gyro biases. Besides, a novel attractive manifold control method is also proposed so that the parameter estimation error terms can converge to zeros independent of persistent excitation condition. The proposed attractive manifold control method can be also robust toward external disturbances. The obtained control inputs are continuous and ensure the control performance of the closed-loop system, in the presence of discontinuous communication delays, external disturbances, parameter uncertainties and gyro biases. The effectiveness of the proposed algorithm is verified in the numerical simulations.

Robust adaptive finite-time attitude tracking and synchronization control for multi-spacecraft with actuator saturation

This paper studies a novel robust adaptive finite-time attitude tracking and synchronization control problem for multi-spacecraft with leader-following architecture, actuator saturation, unknown time-varying inertia and disturbance. Aiming at rejecting the influence of uncertainties and disturbances, an adaptive algorithm is proposed with no prior knowledge of inertia. Meanwhile, based on finite-time control, consensus algorithm and graph theory, a robust adaptive and synchronized attitude tracking control law with a dynamic adjustment function is presented to regulate the attitude to a common time-varying desired state in finite time and improve the dynamic property of system. The effectiveness and performance of the designed control approach are demonstrated through numerical simulation results.

Secure communication in wireless sensor networks based on chaos synchronization using adaptive sliding mode control

Due to resource constraints in wireless sensor networks and the presence of unwanted conditions in communication systems and transmission channels, the suggestion of a robust method which provides battery lifetime increment and relative security is of vital importance. This paper considers the secure communication in wireless sensor networks based on new robust adaptive finite time chaos synchronization approach in the presence of noise and uncertainty. For this purpose, the modified Chua oscillators are added to the base station and sensor nodes to generate the chaotic signals. Chaotic signals are impregnated with the noise and uncertainty. At first, we apply the modified independent component analysis to separate the noise from the chaotic signals. Then, using the adaptive finite-time sliding mode controller, a control law and an adaptive parameter-tuning method is proposed to achieve the finite-time chaos synchronization under the noisy conditions and parametric uncertainties. Synchronization between the base station and each of the sensor nodes is realized by multiplying a selection matrix by the specified chaotic signal which is broadcasted by the base station to the sensor nodes. Simulation results are presented to show the effectiveness and applicability of the proposed technique.