Synchronization Controller Design Research Articles

Security-based control design for synchronization of switched reaction diffusion neural networks with hybrid attacks

This study delves into exploring dissipative synchronization for a class of switched neural networks with external disturbances featuring reaction–diffusion terms under the master–slave scheme. Precisely, the addressed network model comprises a hybrid attack model which entails both deception and denial-of-service attacks. Moreover, security-based control is designed to achieve the intended results, wherein in the realm of control design, the likelihood of cyber attacks is dictated by two separate and independent stochastic Bernoulli distributed factors. Meanwhile, the dissipative theory is employed to effectively curb the external disturbances within the network model. Subsequently, by leveraging the Lyapunov stability theory and linear matrix inequality approach, adequate conditions are acquired for ensuring the mean square exponential synchronization and strict (Γ1,Γ2,Γ3)-θ dissipativity of the examined system. Furthermore, the relation for deriving the control gain matrices is set forth in accordance with the acquired criteria. At the end, a numerical example accompanied by simulation results is supplied to vividly demonstrate the efficacy and significance of the acquired theoretical insights.

Enhanced Results on Sampled-Data Synchronization for Chaotic Neural Networks With Actuator Saturation Using Parameterized Control.

This article investigates a novel sampled-data synchronization controller design method for chaotic neural networks (CNNs) with actuator saturation. The proposed method is based on a parameterization approach which reformulates the activation function as the weighted sum of matrices with the weighting functions. Also, controller gain matrices are combined by affinely transformed weighting functions. The enhanced stabilization criterion is formulated in terms of linear matrix inequalities (LMIs) based on the Lyapunov stability theory and weighting function's information. As shown in the comparison results of the bench marking example, the presented method much outperforms previous methods, and thus the enhancement of the proposed parameterized control is verified.

Finite-time funnel synchronization control based on distributed observer for multi-motor driving systems with input saturation

In this article, the finite-time synchronization control problem is developed for multi-motor driving systems with input saturation. A radial basis function (RBF) neural network is utilized to estimate the unknown uncertainties and the disturbances. In contrast to current control strategies, this study proposes a new approach that utilizes a finite-time distributed observer to estimate the reference signal and then uses the estimated signal to design a synchronization controller, which effectively separates the tracking problem from the synchronous controller design. Furthermore, a funnel function is constructed to actualize the state constraints and confine the synchronization error within a specified boundary. Then, a finite-time funnel control protocol is proposed to ensure that each motor follows the estimated reference signal. Eventually, we illustrate the effectiveness of the proposed method through a numerical example.

Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction

AbstractA dual‐motor servo mechanism is a high‐order and strong‐coupling system with unknown nonlinearity, which brings challenges to controller design to realize high‐performance tracking and synchronization. This article proposes a finite‐time command filtered control strategy to address this problem. In tracking control design, finite‐time command filters are adopted to obtain the derivatives of virtual controllers, and the “explosion of complexity” problem in backstepping is thus solved. An improved compensation system is designed to reduce filtering errors. The tracking control is developed based on the combination of finite‐time control and command filtered approach. Moreover, to deal with unknown nonlinearities and uncertainties, fast finite‐time extended state observers are developed to observe lumped disturbances for the load and motor, respectively. In synchronization control design, two opposite control actions are developed using the speed difference to force two motors to rotate synchronously. The finite‐time convergence of the tracking and synchronization errors is proved. The efficiency of the proposed control strategy is verified via experiments conducted on a dual‐motor servo turntable.

Observer‐based hybrid triggered control design for cluster synchronization of nonlinear complex dynamical networks

SummaryThe issues of cluster synchronization and state estimation for a class of nonlinear complex dynamical networks are concurrently focused in this study. In precise, led by the design of complex dynamical networks, a proportional integral‐based observer is implemented for achieving robustness, by the virtue of which the states of examined networks are estimated. Thereupon, a proportional integral observer‐based hybrid triggered control scheme is proposed, wherein, the switch‐over between time‐ and event‐ triggered scheme is governed through a Bernoulli distributed random variable. Further, with the application of mixed and passivity performance technique, the external disturbances for the addressed complex dynamical networks are reduced. Based on the Lyapunov stability theory, the requisite sufficient conditions in respect of linear matrix inequalities are provided which ensures the discussed complex dynamical network's synchronization phenomenon. In a further, the presented criteria are exploited for the attainment of required controller, proportional and integral gain matrices. In conclusion, the applicability of proposed results and efficacy of the undertaken strategy are evidently proven with the illustration of two numerical examples with Chua's circuit and Goodwin oscillator model.

Analysis and synchronization controller design of dual-port grid-forming voltage-source converters for different operation modes

Analysis and synchronization controller design of dual-port grid-forming voltage-source converters for different operation modes

Coopetition-dependent controller design for bipartite synchronization of cooperation–competition delayed memristive neural networks

In this paper, the bipartite synchronization problem for cooperation–competition delayed memristive neural networks (CCDMNNs) is addressed via designing a coopetition-dependent controller. Based on the coordinate transformation technique, an easy-to-analyze error system is constructed in the presence of cooperation–competition interactions. Two control strategies are proposed respectively to realize bipartite synchronization. First of all, a coopetition-dependent controller that can eliminate the impact of cooperation–competition interactions as well as the time-varying state-dependent memristive connection weights is designed. In combination with inequality techniques, the Lyapunov theory and the interval matrix method, an LMI-form criterion is established to ensure the bipartite synchronization of CCDMNNs. Moreover, an adaptive controller that can automatically adjusts the control parameters to achieve appropriate control gains is proposed to further improve the control performance. Finally, a numerical example is given to verify the correctness and superiority of the proposed control schemes.

Adaptive Drive-Response Synchronization of Timescale-Type Neural Networks With Unbounded Time-Varying Delays.

In recent years, adaptive drive-response synchronization (DRS) of two continuous-time delayed neural networks (NNs) has been investigated extensively. For two timescale-type NNs (TNNs), how to develop adaptive synchronization control schemes and demonstrate rigorously is still an open problem. This article concentrates on adaptive control design for synchronization of TNNs with unbounded time-varying delays. First, timescale-type Barbalat lemma and novel timescale-type inequality techniques are first proposed, which provides us practical methods to investigate timescale-type nonlinear systems. Second, using timescale-type calculus, novel timescale-type inequality, and timescale-type Barbalat lemma, we demonstrate that global asymptotic synchronization can be achieved via adaptive control under algebraic and matrix inequality criteria even if the time-varying delays are unbounded and nondifferentiable. Adaptive DRS is discussed for TNNs, which implies our control schemes are suitable for continuous-time NNs, their discrete-time counterparts, and any combination of them. Finally, numerical examples on TNNs and timescale-type chaotic Ikeda-like oscillator with unbounded time-varying delays are carried out to verify the adaptive control schemes.

Novel criteria of sampled-data synchronization controller design for gated recurrent unit neural networks under mismatched parameters

Synchronization between neural networks (NNs) has been intensively investigated to analyze stability, convergence properties, neuronal behaviors and response to various inputs. However, synchronization techniques of NNs with gated recurrent units (GRUs) have not been provided until now due to their complicated nonlinearity. In this paper, we address the sampled-data synchronization problems of GRUs for the first time, and propose controller design methods using discretely sampled control inputs to synchronize master and slave GRUs. The master and slave GRUs are mathematically modeled as a linear parameter varying (LPV) system in which the parameter of the slave GRUs is constructed independently of the master GRUs. This distinctive modeling feature provides flexibility to extend the existing master and slave NNs into a more general structure. Indeed, the sampled-data synchronization can be achieved by formulating the design condition in terms of linear matrix inequalities (LMIs). The novel sampled-data synchronization criteria are devised by combining the H∞ controller design with the looped-functional approach. The synthesized synchronization controllers guarantee not only asymptotic stability of the synchronization error system with aperiodic sampling, but also provides a satisfactory H∞ control performance. Moreover, the communication efficiency is improved by using the proposed method in which the sampled-data synchronization controller is combined with the event-triggered mechanism. Finally, the numerical example validates the proposed theoretical contributions via simulation results.

Adaptive Event-Triggered Mechanism to Synchronization of Reaction–Diffusion CVNNs and Its Application in Image Secure Communication

This article is centered on the formulation of a refined adaptive sampled-data-based event-triggering control (ASDBETC) scheme for the synchronization of reaction–diffusion complex-valued neural networks (RDCVNNs) with probabilistic time-varying delays (TVDs). A refined ASDBETC mechanism is first proposed in a hierarchy structure, which differs from some conventional sampled-data-based event-triggering control mechanisms with preordained invariable threshold. The refined ASDBETC mechanism can adaptively adjust the orientation and frequency of event-triggered threshold parameters via the variational tendency of states and the corresponding Euclidean distance between states. Therefore, an intact bidirectional regulative mechanism that is sensitive to the changes of state is legitimately established to provide additional flexibility, which is conducive to better compromise between communication resources and control performance. Through considering the effect of uncertainties, the random TVDs belonging to two different intervals by a probabilistic form are introduced. Then, by leveraging a novel time-related Lyapunov–Krasovskii functional (LKF) that contains the more realistic sampled behaviors on the entire sampled interval, new synchronization conditions and controller design method are derived for RDCVNNs. Finally, the advantages of the refined ASDBETC strategy, the availability, and practicability of the developed theories are corroborated via two simulation examples.

Design of sensorless permanent magnet synchronous motor controller based on improved sliding mode observer

Because PMSM needs to install a position sensor in practical application, and the buffeting issue in sensorless control stems from an old SMO (sliding mode observer), an improved SMO is proposed. Stemming from the improvement of the switching function and low-pass filter of the traditional SMO, the chattering problem of the conventional SMO is optimized. Considering the reality that the traditional PI control strategy unable to respond accurately and quickly in the case of current coupling, the current complete decoupling integrates the traditional PI control method is adopted. It can speed up system response and improve system performance. The experimental consequence demonstrates that the improved SMO can effectively restrain the chattering phenomenon and realize the fast and precise control of the PMSM.

H∞ synchronization of Markov jump neural networks with MPDT switching transition probabilities under DoS attacks

In this paper, the synchronization issue of discrete‐time Markov jump neural networks under DoS attacks is studied, in which the transition probability of the Markov chain is considered as time‐varying governed by a mode‐dependent persistent dwell‐time switching rule. The purpose of this paper is to design a suitable controller such that mean‐square exponentially stable of the synchronization error system can be accomplished, and an performance is satisfied under denial of service (DoS) attacks. In order to reduce the conservatism of obtained results, some synchronization analysis criteria are obtained by adopting an activation function division method. Based on these criteria, an effective security synchronization controller design method is presented. Conclusively, an example is given to verify the validity of the results.

Synchronization of Delayed Fuzzy Neural Networks with Probabilistic Communication Delay and Its Application to Image Encryption

This article studies the design of fuzzy synchronization controller of Takagi—Sugeno (T-S) fuzzy neural networks with distributed time-varying delay and probabilistic network communication delay. Compared with the existing model of neural networks with distributed time-varying delay without kernel, a more general model containing a distributed delay kernel is considered. By utilizing the probability distribution of random communication delays, a distributed but deterministic delay model is established. In this model, the delay probability density function is treated as the distributed delay kernel. By developing a new Lyapunov-Krasovskii functional (LKF) related to the distributed delay kernels and using an integral inequality, new sufficient conditions for the existence of a synchronization controller are presented. Finally, a numerical simulation and an application of encrypting the image are carried out to illustrate the effectiveness of the developed strategy.

The Synchronization of Networked Harmonic Oscillators Under Denial-of-Service Attacks

This article is concerned with resilient control design for synchronization of multiple harmonic oscillators coupled via vulnerable network suffering from denial-of-service (DoS) attacks. The synchronization of multiple harmonic oscillators can be achieved under consideration of certain DoS attacks. A distinct resilient distributed control protocol is designed for individual harmonic oscillator by proposing a resilient logical packet processor (RLPP). Some sufficient conditions on the duration and frequency of attacks reflected by the bounds of lumped time-varying delay are derived by employing complete-type Lyapunov–Krasovskii functionals (LKFs). The gain matrix can be designed by solving a set of linear matrix inequalities by combining an optimization algorithm. Finally, the proposed synchronization control scheme is applied to a representative model of the single-phase photovoltaic grid interconnection process. Numerical simulations are provided to show the effectiveness of the developed method.

Dynamic event-triggered control for intra/inter-layer synchronization in multi-layer networks

In this paper, intra-layer synchronization (ALS) and inter-layer synchronization (RLS) of multi-layer networks (MLNs) are studied, where the topology of each layer is different and the inter-layer connection is node-to-node if two layers are connected. Dynamic event-triggered (DET) control is first introduced into the design of synchronization controllers in MLNs to reduce communication frequency. Based on the Lyapunov functional method, sufficient conditions for ALS and RLS are strictly derived by designing appropriate DET controllers. It is theoretically verified that the designed DET conditions in MLNs further reduce triggering frequency compared with static event-triggered (SET) conditions, and Zeno phenomenon can be eliminated. Finally, the validity of the theoretical results is illustrated by numerical simulations.

Balancing and Tracking Control of Ballbot Mobile Robots Using a Novel Synchronization Controller Along With Online System Identification

Ballbots are omnidirectional self-balancing platforms that can be exploited in many applications to detect, track, or interact with objects or humans, such as a service robot. Ballbot will enable mobile robots to stand tall and move elegantly through busy environments. However, maintaining equilibrium through synchronization of motion between the ball and the body of a Ballbot is still an open research problem. This article presents a synchronization control (SC) design, with synchronization and coupling errors for Ballbots to stabilize the body and control ball transfer simultaneously. The proposed SC method is applied to the two 2-D planar models of a Ballbot robot. The dynamic model of the Ballbot is derived, and parameters are identified online using the intelligent particle swarm optimization method. The proposed controller is proven to guarantee asymptotic convergence to zero errors in tracking and synchronization. The stabilizing and transferring problems are investigated through several simulations and experiments by using an actual Ballbot platform. Moreover, the controller performance is compared with an augmented proportional derivative controller and a partial feedback linearization controller. The results and comparisons demonstrate a superior stabilization accuracy of the proposed SC method.

State Estimation-Based Hybrid-Triggered Controller Design for Synchronization of Repeated Scalar Nonlinear Complex Dynamical Networks

The goal of this work is to examine the issue of state estimation-based synchronization of nonlinear complex dynamical networks that are prone to external disturbances, repeated scalar nonlinearities and time-varying coupling delays. In a nutshell, hybrid-triggered communication transmission nonfragile control design with respect to the estimated states and extended dissipative theory is designed, which comprises of both the time and event-triggered mechanisms, and a hybrid generator is presented between the sensor and controller. More preciously, a stochastic variable satisfying the Bernoulli random binary distribution is utilized to represent the phenomenon of random transmission between the time and event-triggered mechanism. Furthermore, delay-dependent adequate conditions for ensuring the synchronization of the addressed system are developed in the form of linear matrix inequalities. And, the requisite gain matrices and hybrid-triggered parameters are evaluated with the help of solving these procured conditions. Lastly, a numerical example with an application to memristor-based Chua’s circuit model is demonstrated to ensure the effectiveness of established control technique.

Phaser-Based Transfer Function Analysis of Power Synchronization Control Instability for a Grid Forming Inverter in a Stiff Grid

The grid forming inverter (GFM) is considered a key technology to solve the issues of inverter-based resource (IBR)-rich grids. Many studies have investigated how GFM affects and improves power system stability. However, few studies have considered the instability of GFM as it relates to various grid conditions. This paper discusses the mechanism of power synchronization control instability of GFM by conducting transfer function analysis with focus on various grid conditions, the control logic of GFM, and relevant parameter setting. Based on the above analysis, a procedure for power synchronization controller design of GFM is proposed. Experimental tests in the control hardware in the loop (CHIL) environment are performed to verify the validity of the transfer function analysis and reveal that the instability of GFM is likely to occur when it is connected to stiff grids or experiences a larger phase delay due to a longer power measurement delay and lower damping of the controller.

Robust complete synchronization control design for non‐collocated nonlinear master–slave system over delayed communication network

AbstractIn this article, a predictor‐based robust synchronization control scheme is proposed for a non‐collocated nonlinear master–slave system with any large networked communication time delays. In contrast to traditional collocated teleoperation systems, enhanced flexibility, and operation capacity will be obtained under the non‐collocated system structure in this article. Yet, due to the introduced input delays, existing control strategies for teleoperation systems are no longer applicable. Aiming at this problem, the terminal sliding mode (TSM) admittance control approach is proposed for the master robot to improve system transparency by receiving the contact force from the slave robot to the local side, first. Moreover, complete position synchronization performance is realized by developing a predictor‐based TSM control method for the slave robot while the closed‐loop system is subject to time‐variant large delays. It is mathematically proved that the synchronization errors between the master and the slave will converge to zero completely in finite time by compensating the effect of time delays. Finally, numerical simulations and comparisons are executed to illustrate the superior performance of the posed control algorithms.

Mixed [formula omitted]/passive synchronization for persistent dwell-time switched neural networks via an activation function dividing method

The mixed H∞/passive synchronization issue of discrete-time switched neural networks is studied in this paper. In order to regulate the switching between subsystems, the persistent dwell-time switching law is adopted. The paper aims to design a suitable synchronization controller to make the synchronization error system satisfy the mixed H∞/passive performance and achieve global uniform exponential stability. By employing Lyapunov stability theory, performance analysis criteria and the synchronization controller design method are given, in which an activation function dividing method is employed to reduce their conservatism. Simulation results demonstrate the superiority and effectiveness of the method.