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This paper addresses the adaptive event-triggered non-fragile output pinning synchronization control for complex networks subject to random saturations and cyber-attacks. An adaptive event-triggered scheme (AETS) based on the output synchronization error is proposed to save network bandwidth, and a pinning control strategy is employed to reduce the input of control signal. Considering the effect of AETS, randomly occurring saturations and cyber-attacks on the drive and response systems, we investigate a novel output security synchronization error model, and then design an event-triggered non-fragile controller such that the asymptotic stability of the error system can be guaranteed. Meanwhile, we obtain the controller gains and event-triggered matrices in terms of solving the linear matrix inequalities (LMIs). Finally, a simulation example is provided to verify the design method.

In this technical note, the problem of observer-based controller design is considered for sensor networked systems subject to distributed hybrid-triggered transmission scheme and input quantisation. A novel observer model based on coupled transmission signals from multi-channel is first proposed to estimate unavailable state variables and exploited in the feedback protocol. In order to provide a trade-off between saving network resources and improving system performance, a distributed hybrid-triggered transmission scheme with communication delays is adopted to update the observer input signals. For the sake of further reducing the occupancy of network resources, the control input signal is quantised by a logarithmic quantiser. Then, by making use of the Lyapunov stability theory, the sufficient conditions guaranteeing the system asymptotically stable are presented. Moreover, the explicit expressions of observer and controller parameters are achieved by solving a set of linear matrix inequalities. Finally, two simulation examples are provided to illustrate the rationality of the proposed control method.

This paper is engaged in investigating the observer-based event-triggered output feedback control issue for fractional-order cyber–physical systems with stochastic network attacks, where the order scale of the fractional derivative used is 0 α 1 . An event-triggered scheme (ETS) with output-independent threshold is proposed to renew the observer input so as to reduce the redundant data communications. Considering the effects of the ETS and network attacks, a novel closed-loop fractional-order control system model is constructed. By making use of fractional-order Lyapunov indirect approach, sufficient conditions that can insure the global stochastic asymptotic stability of the established closed-loop control system are obtained. Moreover, according to the singular value decomposition (SVD) of matrix, the co-design of the gains of the desired observer and controller is addressed by finding the solution of the linear matrix inequalities (LMIs). Finally, a numerical example and a diesel engine control system are provided to validate the feasibility of the adopted observer-based control method.

This paper investigates the event-triggered drive-response synchronization control for T–S fuzzy neural networked systems with time delay. In order to save network resources and improve transmission efficiency, an error output-dependent event-triggering scheme is proposed, which can determine whether the measurement errors should be transmitted to the controller or not. For the purpose of studying the synchronization problem under the given event-triggering scheme, a novel T–S model of synchronous control based on the drive-response mode is proposed. By using the Lyapunov–krasovskii functional method, sufficient conditions are obtained to guarantee the asymptotic stability of the synchronization error systems. Moreover, by solving some linear matrix inequalities (LMIs), a set of controllers for the response systems can be achieved explicitly. Finally, two numerical examples are provided to illustrate effectiveness of the proposed method.

In order to improve the fault diagnosis theory of switched systems, observer-based method is proposed to deal with the fault diagnosis issue subjected to the parameter uncertainty, unknown process disturbances and unexpected faults. By employing proportional-integral observer (PIO) technique and the average dwell-time (ADT) method, an H∞/H− performance level is considered to ensure the worst case of robustness to the disturbance and sensitivity to the fault simultaneously. Moreover, the obtained fault diagnosis observer can give accurate fault estimation online for the piecewise constant fault. Finally, a two-tank system example is introduced in the end to show the effectiveness of the proposed results.

This paper investigates the adaptive event-triggered synchronization control problem for a class of complex networks with quantization and cyber-attacks. For reducing the burden of communication and computation, an adaptive event-triggered scheme and a logarithmic quantizer are both introduced. Firstly, considering the effect of adaptive event-triggered sampling, quantization and cyber-attacks, a novel synchronization error model is established. By using Lyapunov functional method, some sufficient conditions are derived to guarantee the asymptotic stability of the augmented synchronization error system. Moreover, the co-design of the controller and adaptive event-triggered scheme are also solved in terms of solving the solution of linear matrix inequality(LMI). Finally, a numerical example is exploited to show the effectiveness of the proposed method.

This paper investigates the issue of decentralized control for interconnected semi-Markovian systems with partially accessible transition rates (TRs). Firstly, a dynamic system model with a memory event-triggered mechanism (METM) is designed, which can effectively improve the fault tolerance of the event-triggering mechanism by employing the historical trigger data. Then a state feedback control model with dynamic METM is constructed, in which the semi-Markovian parameters with completely unknown and partially known transition probabilities are considered. Some sufficient conditions that insure the stochastic stability of the interconnected semi-Markovian systems can be obtained by utilizing the Lyapunov function and suitable model transformations method. Meanwhile, the parameters and the controller gain matrices of dynamic METM are also solved simultaneously by applying the linear matrix inequalities (LMIs). Finally, a simulation example is given to verify the effectiveness of the proposed method.

The paper is concerned with the observer-based robust control problem for fractional-order (FO) nonlinear uncertain systems subject to control input saturation and measurement quantization, in which the fractional commensurate order satisfies α ∈ ( 0 , 1 ) . The state measurements of observer are quantized by a logarithmic quantizer. Firstly, by introducing a continuous frequency distributed equivalent model of fractional integrator, sufficient condition for guaranteeing the asymptotic stability of closed-loop FO systems is established via the indirect Lyapunov approach. Then, by using matrix’s singular value decomposition (SVD) and linear matrix inequality (LMI) technique, the co-design problem of desired observer and controller gains are derived, which will be shown that the solution guarantees the stability of closed-loop FO nonlinear uncertain control systems. Finally, a simulation example is given to illustrate the validity of this method.

This paper investigates the problem of consensus tracking control for multi-agent systems with stochastic actuator faults, where the asynchronous adaptive event-triggered scheme (AETS) is proposed to reduce communication burden. The failure phenomenon for each actuator is described by an independent and identically distributed (i.i.d) random process. The communication information is divided two groups according to the scenario whether the followers can receive the information from the leader or not. Two adaptive event-triggered communication schemes are introduced based on the above classified information. Considering the stochastic actuator faults and the designed AETS, a new closed-loop fault-tolerant tracking control system model is established. Then, by employing the Lyapunov stability theory and stochastic analysis technique, a new fault-dependent stability criterion is derived, which ensures that the leader-following tracking error system is stochastically mean-square stable. Based on this criterion, the fault-tolerant consensus controller gains and the triggering parameters are obtained simultaneously by solving a linear matrix inequality (LMI). Moreover, the Zeno behavior of the AETS is excluded. Finally, a simulation example is included to illustrate the effectiveness of theoretical results.

This paper is concerned with the adaptive event-triggered robust state estimation for a class of fractional-order nonlinear uncertain systems, where the fractional order satisfies 0

Under the consideration of distributed adaptive event-triggered communication scheme and cyber-attacks, the paper focuses the observer-based H ∞ control issue for Markov jump linear systems over stochastic saturation sensor networks. To describe physical systems with abrupt variations, the system parameters and the network structure composed of a group of sensor nodes are modeled by Markovian switching topologies. A distributed adaptive event-triggered mechanism is designed to reduce the occupancy of the limited network resources. Based on randomly occurring cyber-attacks, a novel observer collected coupled transmission signals from multi-channel is first proposed to estimate unavailable state variables and exploited in the feedback protocol. Furthermore, a sufficient condition is derived to guarantee the stability of the built model with a prescribed performance index. Simultaneously, a co-design method for observer and controller gain matrices is proposed. Finally, the effectiveness of the model is illustrated by a numerical simulation example.

This paper is concerned with the distributed hybrid-triggered H∞ filter design problem for sensor networked systems (SNSs) with the output saturations. A distributed hybrid-triggered transmission scheme (DHTTS) is proposed to work in term of time-trigger and event-trigger switching, which can get a balance of saving network resources and improving system performance. Firstly, combining hybrid-triggered scheme and output saturation, the distributed H∞ filtering error system with communication delays is modeled. Then, by using Lyapunov–Krasovskii functional method and linear matrix inequality technique, some sufficient conditions for guaranteeing the asymptotic stability and average H∞ performance of the filtering error system are established, and the distributed filter parameters and hybrid-trigger matrix parameters can be obtained simultaneously. Finally, a simulation example is provided to illustrate the effectiveness of the developed method.

This paper is concerned with the state feedback H∞ control problem for hybrid-triggered networked control systems (NCSs) with stochastic nonlinearity and state quantization. In order to establish a higher utilization of the network resources, a hybrid-triggered transmission scheme (HTTS) and measurement size reduction scheme are introduced. Firstly, the HTTS is presented such that the signal can be transmitted according to the law. Then the measurement size reduction scheme, i.e., the logarithmic quantization is applied. Then, considering the effect of HTTS and quantization, the original NCSs model is reformulated as a new hybrid-triggered NCSs with communication delay. By using Lyapunov functional method and linear matrix inequality technique, sufficient conditions for stochastical stability with a prescribed H∞ performance level are established, and the design of controller and trigger parameters can be obtained. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

A distributed hybrid-triggered $H_\infty$ state estimation is investigated for a class of complex networked systems under networked adversarial attacks. First, we propose a hybrid-triggered communication scheme to achieve the right balance between improving the performance of the basic event-triggered scheme and reducing the network burden. Under the hybrid triggered communication scheme, a novel state estimation model is established that assembles the items of triggered functions and networked adversarial attacks. Then, by using a stochastic analysis technique and the Lyapunov stability theory, some sufficient conditions for the stochastic stability of systems are obtained. In addition, a set of desired $H_\infty$ estimation gains and trigger parameters can be simultaneously derived by solving some linear matrix inequalities. Finally, a numerical example including five nodes is provided to demonstrate the effectiveness of the proposed approach.

This paper addresses the problem of H ∞ filter design for T-S fuzzy systems with saturation nonlinearities. For the purpose of reducing network burden, an output-dependent triggering scheme and a quantizer are introduced at the same time. The output-dependent triggering scheme is applied to determine whether or not the current instant information should be transmitted to the quantizer. Saturation nonlinearities, as a common phenomenon in networked systems due to the physical or technological constraints, is also considered here. Then a filtering error model with aforementioned characteristics is established. By using Lyapunov functional approach and stochastic analysis techniques, some matrix inequality-based sufficient conditions for the existence of the fuzzy filter are obtained. Moreover, a co-design algorithm for solving the suitable filter and the event generator is derived. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.

The existing overlap singularities in the parameter space significantly affect the learning dynamics of the multilayer perceptrons. From the obtained theoretical learning trajectories near overlap singularity, when the learning process has been affected by the overlap singularity, the influence area of the overlap singularity is just the line space where the two hidden units equal to each other. However, in the practical applications, different case has been observed and the influence area of such singularity may be larger. By analyzing the generalization error of multilayer perceptrons, we find that the error surface is much flatter near overlap singularity and the singularity would have much larger influence area. Finally, the validity of the obtained results are verified by taking an artificial experiment and two real-data experiments.

This paper investigates the state estimation problem of Markovian jump systems with time-varying delay. The purpose is to design a state estimator to estimate system states through available output measurements. A novel event-triggered scheme is proposed, which is used to determine whether the sampled state information should be transmitted. The main idea is that the proposed event-triggered scheme provides a supervision of the system state in discrete instants and the newly sampled sensor measurements violating specified triggering condition will be transmitted to the estimator. Firstly, a state estimation model is constructed which describes the transmission delay, Markov parameters and an event-triggered mechanism in a unified framework. Secondly, based on the model, the criteria for the exponential mean square stability are proposed by using Lyapunov functional method and convexity property of the matrix inequality. Under the obtained conditions and the event-triggered scheme, the desired state estimator of Markovian jump systems with time delay is established by solving some linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

This paper studies event-driven synchronization control problem for chaotic Lur'e system with cyber attack. Firstly, In order to save network bandwidth resources, the event-driven scheme is employed to determine whether the sampled state should be transmitted to the controller. Secondly, a synchronization error model is designed to describe the master-slave synchronization system with event-driven scheme and cyber attack. Thirdly, based on Lyapunov functional approach, sufficient conditions for stabilization are derived which can ensure synchronization of the master system and slave system; particularly, a co-designed approach of controller and the event-driven matrix is obtained using the above stability condition. Lastly, a numerical example is presented to illustrate the effectiveness of the proposed approach.

This paper discusses event-driven synchronization control problem for chaotic neural networks subject to actuator saturation. Firstly, in order to reduce the load of network, the event-driven scheme is introduced to determine whether the sampled state should be sent to the controller. Secondly, a synchronization error model is constructed to describe the master-slave synchronization system with event-driven scheme and actuator saturation in a unified framework. Thirdly, based on Lyapunov-Krasovskii functional, sufficient conditions for stabilization are obtained which can ensure synchronization of the master system and slave system; particularly, co-design of controller and the event-triggered matrix is achieved based on the above stability condition. Lastly, a numerical example is presented to show the effectiveness of the proposed approach.

By using hybrid-triggered method, this paper investigates the distributed $H_{\infty}$ filter design problem for networked control systems (NCSs) over sensor network with output saturations. The distributed hybrid-triggered transmission scheme (DHTTS) under the sensor output saturations is first proposed to solve the filter design, which can get a balance of saving network resources and improving systems performance. Firstly, the distributed $H_{\infty}$ filtering error systems with communication delays is modeled under DHTTS. Then, by using Lyapunov-Krasovskii functional methods and linear matrix inequality (LMI) techniques, sufficient conditions for guaranteeing the asymptotic stability of the distributed $H_{\infty}$ filtering error systems are established, and the distributed filters parameters and hybrid-trigger matrix parameters can be obtained simultaneously. Finally, a simulation example is provided to illustrate the effectiveness of the developed method.

This paper studies co-design of event generator and synchronous controller for chaotic neural networks with quantization. A quantized event-triggered scheme is presented to reduce the load of network transmission. Sufficient stabilization conditions for synchronization error system are derived on the basis of Lyapunov-Krasovskii functional. Based on the above stability condition, a co-designed parameters of controller and the corresponding event-triggered parameters are obtained. Finally, a numerical example is employed to illustrate the effectiveness of the proposed control method.

This paper is concerned with the state estimation problem for hybrid-triggered networked control systems (NCSs) with stochastic nonlinearity and quantization. In order to establish a higher utilization of the network resources, a hybrid-triggered transmission scheme (HTTS) and measurement size reduction scheme are introduced. Firstly, the HTTS is presented such that the signal can be transmitted according to the law, and the measurement size reduction scheme, i.e., the quantization is applied. Then, considering the effect of HTTS and quantization, the original NCSs model is reformulated as a new hybrid-triggered state estimation systems with communication delay. By using Lyapunov functional method and linear matrix inequality technique, sufficient conditions for system stability with a prescribed H œ performance level are established, and the design of state estimator and hybrid trigger parameters can be obtained. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

This paper investigates the problem of dynamic output feedback fault tolerant controller design for discrete-time switched systems with actuator fault. By using reduced-order observer method and switched Lyapunov function technique, a fault estimation algorithm is achieved for the discrete-time switched system with actuator fault. Then based on the obtained online fault estimation information, a switched dynamic output feedback fault tolerant controller is employed to compensate for the effect of faults by stabilizing the closed-loop systems. Finally, an example is proposed to illustrate the obtained results.

In this paper, the event-based H ∞ filtering problem is investigated for a Takagi-Sugeno(T-S) fuzzy systems with randomly occurring sensor saturations(ROSS). For the purpose of reducing communication, an event-triggered scheme is introduced to the networked control systems. Under this scheme, the sensor dada will be transmitted only when the sampled measurements violating specified triggering conditions. A new phenomenon of randomly occurring sensor saturations is put forward in order to better reflect the reality in the networked such as randomly occurring incomplete information. A novel filter design model for T-S fuzzy systems is established to account for both randomly occurring sensor saturations and event-triggered scheme. By utilizing the stochastic analysis techniques and Lyapunov functional approach, sufficient conditions for the existence of the desired filter are derived in term of linear matrix inequalities(LMIs) to satisfy the prescribed H ∞ performance requirement. Moreover, the explicit expression is given for the designed filter parameters. Finally, a numerical example is employed to show the effectiveness of filtering scheme designed.

The event-triggered state estimation is investigated for a class of complex networks system with randomly nonlinearities. A novel event-triggered scheme is proposed, which can reduce the information communication burden in the network. Considering the effect of transmission delay, a time-varying delayed system model is constructed. Attention of this paper is focused on the analysis and design of a reliable estimator for the complex networks through the available output measurements under event-triggered scheme. In order to design the state estimator, a Lyapunov functional approach and the linear matrix inequality technique are employed. A sufficient condition is obtained in which the estimator error dynamics is exponential asymptotically stable, and a state estimator of considered complex networks can be achieved by solving some linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

In data mining, fuzzy C-means clustering algorithm has demonstrated advantage in dealing with the challenges posed by large collections of vague and uncertain data. This paper reviews concept of fuzzy C-means clustering which is widely used in context of pattern recognition. Based on the study of the fuzzy C-means algorithm, we propose a weighted local fuzzy regression model. The efficiency of the new modified model is demonstrated on real data from 1980 to 2010 collected for road freight of China. And with this method, analysis of correlation between economic development, transport facilities and demand for road transport is given. At last, we apply this method to predict the demand for road freight of China from 2011 to 2013. The results shown that weighed fuzzy model has more practical value than least squares regression on prediction problems with the small sample, non-linear and high-dimensional pattern recognition of transport system.