Load frequency control for wind-integrated multi-area power systems: An area-based event-triggered sliding mode scheme

This paper deals with the load frequency control problem of multi-area power system with doubly-fed-induction-generator-based wind farm. An area-based event-triggered (ET) sliding mode control scheme is proposed to restore the nominal frequency by transmitting less information. The main feature of area-based ET scheme is that each area will transmit its states information to the controller independently via its own triggering mechanism. By flexibly selecting triggering thresholds, the area-based ET scheme can meet the unbalanced network resources among different areas. Meanwhile, the designed sliding mode controller can effectively suppress the fast fluctuation resulting from load and wind generation to achieve frequency restoration and maintain the tie-line power at its scheduled value. The optimization algorithm on the sufficient conditions is given. Finally, the proposed control scheme is illustrated via a three-area power system and IEEE 39-bus system.     

Load frequency control for multi-area power system based on Markov model

The usage of communication networks provides a backbone of integration of information technologies and load frequency control (LFC) scheme. Time delays introduced by network environments taking the new challenge for dynamic performances and even the stability of closed-loop LFC scheme. This paper focuses on the stability and stabilization of multi-area LFC schemes for power systems with the introduction of communication networks and renewable energies. Markov theory is exploited in this paper for describing the discrete time-delay mechanism. Then, by utilizing Wirtinger-based inequality, and constructing a novel Lyapunov functions, the results of robust stability and stabilization criteria are derived in terms of linear matrix inequality (LMI). Finally, simulation results are provided to demonstrate the effectiveness and superiority of developed results.     

Event-triggered H∞ filtering control for a class of distributed parameter systems with Markovian switching topology

The H_∞ filtering problem for distributed parameter systems with stochastic switching topology is investigated in this paper based on event-triggered control scheme. The switching topology which subjects to a Markovian chain is considered in filter design because of the communication uncertainty of practical networks. An event-triggered mechanism as a sampling scheme is developed aiming at the benefit of reducing the computation load or saving the limited network resources. Based on some novel integral inequalities, the improved delayed method is proposed for the H_∞ filtering control problem with event-triggered scheme. Moreover, by employing stochastic stability theory, filters with Markovian jump parameters are designed to guarantee that the stochastically mean square stability and H_∞ performance of the underlying error system. Finally, in order to illustrate the applicability of the obtained results, numerical examples are presented.     

Distributed event-triggered control for networked control systems with stochastic cyber-attacks

This paper is concerned with the problem of distributed event-triggered controller design for networked control systems (NCSs) with stochastic cyber-attacks. A decentralized event-triggered scheme is introduced to save the energy consumption and alleviate the transmission load of the network. Each sensor can make its own decision to determine whether the sampled data is delivered to the network or not. By taking two kinds of random cyber-attacks into consideration, a novel mathematical model is constructed for distributed event-triggered NCSs. Sufficient conditions which can guarantee the stability of the control system are obtained by applying Lyapunov stability theory, and the design method of the controller gain is presented in an exact expression. Finally, an example is given to demonstrate the effectiveness of the proposed method.     

Decentralized event-triggered finite-time attitude consensus control of multiple spacecraft under directed graph

This article investigates the finite-time consensus problem for the attitude system of multiple spacecraft under directed graph, where the communication bandwidth constraint, inertia matrix uncertainties and external disturbances are considered. An event-triggered communication mechanism is developed to address the problem of communication bandwidth constraint. In this event-triggered mechanism, spacecraft sends their attitude information to their neighbors only when the given event is triggered. Furthermore, an adaptive law is designed to counteract the effect of inertia matrix uncertainties and external disturbances. Then, a finite-time attitude consensus tracking control scheme is proposed based on the event-triggered communication mechanism and adaptive law. The proposed control scheme can guarantee the finite-time stability and convergence of the multiple spacecraft systems and exclude the Zeno phenomenon. Finally, simulation results validate the effectiveness of the proposed control scheme.     

Population extremal optimization-based extended distributed model predictive load frequency control of multi-area interconnected power systems

How to design a set of optimal distributed load frequency controllers for a multi-area interconnected power system is an important but still challenging issue in the field of modern electric power systems. This paper presents an adaptive population extremal optimization-based extended distributed model predictive load frequency control method called PEO-EDMPC for a multi-area interconnected power system. The key idea behind the proposed method is formulating the dynamic load frequency control issue of each area power system as an extended distributed discrete-time state-space model based on an extended state vector, obtaining a distributed dynamic extended predictive model, and rolling optimization of real-time control output signal by adopting an adaptive population extremal optimization algorithm, where the fitness is evaluated by the weighted sum of square predicted errors and square future control values. The superiority of the proposed PEO-EDMPC method to a traditional distributed model predictive control method, a population extremal optimization-based distributed proportional-integral control algorithm and a traditional distributed integral control method is demonstrated by the simulation studies on two-area and three-area interconnected power systems in cases of normal, perturbed system parameters and dynamical load disturbances.     

Reachable set synthesis for singular systems with time-varying delay via the adaptive event-triggered scheme

This work is concerned with the problem of reachable set synthesis for a class of singular systems with time-varying delay via the adaptive event-triggered scheme. Compared with the static event-triggered mechanism, the adaptive event-triggered mechanism can save the communication resources more effectively. By virtue of Lyapunov stability theory, sufficient conditions are given to guarantee the stability of the closed-loop system and that the reachable set of the resulting system is bounded by the obtained ellipsoid. In addition, by using linear matrix inequality technique and free-weighting matrix method, the weighting matrix of event-triggered condition and proportional-derivative (P-D) feedback controller gains are obtained. The effectiveness and superiority of the developed control approach are substantiated by a numerical example and two practical examples.     

Event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks

This paper investigates the event-based control for networked T-S fuzzy cascade control systems with quantization and cyber attacks. In order to solve the problem of limited communication resources, an event-triggered scheme and a quantization mechanism are adopted, which can effectively reduce the burden of communication and save the network resources of the system. By considering the influence of cyber attacks, a newly quantized T-S fuzzy model for networked cascade control systems (NCCSs) under the event-triggered scheme is established. By using the Lyapunov stability theory, sufficient conditions guaranteeing the asymptotical stability of networked T-S fuzzy cascade control systems are obtained. In addition, the controller gains are derived by solving a set of linear matrix inequalities. Finally, a numerical example is presented to verify the validity of the proposed method.     

Constrained load/frequency control problems in networked multi-area power systems

In this paper, we present a supervisory discrete-time predictive control strategy for load/frequency control problems in networked multi-area power systems subject to coordination constraints. Coordination between the control center and the spatially distributed areas is accomplished via data networks subject to communication latency modeled by time-varying time-delay. The aim here is finding supervising strategies able to reconfigure, whenever necessary in response to unexpected load changes and/or faults, the nominal set-points on frequency and generated power to the generators of each area so that viable evolutions would arise for the overall power system and a new sustainable equilibrium is reached. In order to demonstrate the effectiveness of the strategy, examples on a four-area power system are presented.     

Event-triggered stabilisation for stochastic delayed differential systems with exogenous disturbances

In this paper, the practically input-to-state stabilization issue is considered for the stochastic delayed differential systems (SDDSs) with exogenous disturbances. To reduce the transmission frequency of the feedback control signal, the proposed SDDSs are stabilized by an event-triggered strategy. The concept of the practically input-to-state stability (ISS) is used to describe the dynamic performance of control target in the event-triggered schemes and exogenous disturbances. Besides, the considered SDDSs is stabilized by an event-triggered feedback controller which is represented by linear matrix inequalities. Moreover, lower bound of the interaction time of the event-triggered control method is obtained to avoid the Zeno behavior of the proposed event-triggering scheme. Finally, the effectiveness of the conclusion is verified by a numerical example.     

Dynamic quantized control for switched fuzzy singularly perturbation systems with event-triggered protocol

This paper is concerned with the dynamic quantized control for switched fuzzy systems with singular perturbation and an improved event-triggered protocol. Essentially apart from the transition probabilities, the nonhomogeneous sojourn probabilities are employed to characterize the dynamic behavior of switched fuzzy singularly perturbed systems based on a deterministic switching signal. Benefiting from the dynamic quantization parameter, the quantization-based event-triggered protocol is presented, thereby decreasing the communication load. Based on the hidden Markov model, a novel event-triggered asynchronous control law is built. Finally, two examples are shown to clarify the practicality of the obtained results.     

Event-triggered time-varying formation control for general linear multi-agent systems

This paper investigates event-triggered formation control problems for general linear multi-agent systems. The time-varying formation this paper studied can be described by a bounded piecewise differentiable vector-valued function. Firstly, a time-varying formation control protocol based on event-triggered scheme is constructed by the states of the neighboring agents. Each agent broadcasts its state information to neighbor nodes if the triggering condition is satisfied, and the communication load is decreased significantly. Then, an algorithm consisting of three steps is proposed to design the event-triggered formation control protocol. Moreover, it is proven that under the designed event-triggered formation protocol, the multi-agent systems can achieve the desired time-varying formation which belongs to the feasible formation set with the bounded formation error and the closed systems do not exhibit Zeno behavior. Finally, simulation results are given to demonstrate the effectiveness of the theoretical analysis.     

Improved event-triggered control for networked control systems subject to deception attacks

This paper investigates the event-triggered control problem for networked control systems subject to deception attacks. An improved event-triggered scheme is proposed to reduce transmission rate by using both the information of the relative error and the past released signals. Under the proposed event-triggered scheme, a new switched time-delay system model is proposed for the event-triggered control systems. Based on the new model, the exponential mean-square stability criteria are derived by using the constructed Lyapunov function. Then, a co-design method is developed to obtain both trigger parameters and mode-dependent controller gains. Finally, the proposed scheme is verified by an unmanned aerial vehicle system.     

Predefined-time practical consensus for multi-agent systems via event-triggered control

This paper studies the predefined-time practical consensus problem for multiple single-integrator systems through event-triggered control. A new kind of time-varying functions is firstly proposed. Then, new event-triggered control inputs as well as triggering conditions are designed on the basis of the time-varying function and the local broadcasted states. In particular, the control scheme is fully-distributed because no global information of the system and the communication topology is needed. Furthermore, the consensus analysis is presented based on a sufficient condition for predefined-time practical stability. It illustrates that practical consensus can be ensured with a completely pre-specified time. Besides, the exclusion of Zeno behavior at all the time instants is addressed. Numerical results verify the validity of the obtained control method.     

Event-triggered secure control of nonlinear multi-agent systems under sensor attacks

In this paper, a security consistent tracking control scheme with event-triggered strategy and sensor attacks is developed for a class of nonlinear multi-agent systems. For the sensor attacks on the system, a security measurement preselector and a state observer are introduced to combat the impact of the attacks and achieve secure state estimation. In addition, command filtering technology is introduced to overcome the “complexity explosion” caused by the use of the backstepping approach. Subsequently, a new dynamic event-triggered strategy is proposed, in which the triggering conditions are no longer constants but can be adjusted in real time according to the adaptive variables, so that the designed event-triggered mechanism has stronger online update ability. The measurement states are only transmitted through the network based on event-triggered conditions. The proposed adaptive backstepping algorithm not only ensures the security of the system under sensor attacks but also saves network resources and ensures the consistent tracking performance of multi-agent systems. The boundedness of all closed-loop signals is proved by Lyapunov stability analysis. Simulation examples show the effectiveness of the control scheme.     

Event-Triggered formation control for time-delayed discrete-Time multi-Agent system applied to multi-UAV formation flying

This paper studies the formation control for a time-delayed discrete-time multi-agent system (MAS). An event-triggered controller is proposed to reduce the communication load of the system. Based on the designed event-triggered condition and properties of Schur stable matrix, the stability of formation for discrete-time MAS is proved. Utilizing the virtual simulation platform integrated Robot Operating System (ROS) and Gazebo, a virtual scene with unmanned aerial vehicles (UAVs) models is built and the verification for the theoretical algorithm is completed. Finally, an experimental platform with four practical UAVs is constructed and the result shows that the expected formation is achieved and controller proposed can solve the formation control problem for time-delayed discrete-time MASs. Besides, the effectiveness of the event-triggered mechanism on reducing communication frequency is comfirmed in practical scenarios.     

Resilient event-triggered consensus control for nonlinear muti-agent systems with DoS attacks

The distributed event-triggered secure consensus control is discussed for multi-agent systems (MASs) subject to DoS attacks and controller gain variation. In order to reduce unnecessary network traffic in communication channel, a resilient distributed event-triggered scheme is adopted at each agent to decide whether the sampled signal should be transmitted or not. The event-triggered scheme in this paper can be applicable to MASs under denial-of-service (DoS) attacks. We assume the information of DoS attacks, such as the attack period and the consecutive attack duration, can be detected. Under the introduced communication scheme and the occurrence of DoS attacks, a new sufficient condition is achieved which can guarantee the security consensus performance of the established system model. Moreover, the explicit expressions of the triggering matrices and the controller gain are presented. Finally, simulation results are provided to verify the effectiveness of the obtained theoretical results.     

Event-triggered synchronization of delayed neural networks with actuator saturation using quantized measurements

This paper studies event-triggered synchronization control problem for delayed neural networks with quantization and actuator saturation. Firstly, in order to reduce the load of network meanwhile retain required performance of system, the event-triggered scheme is adopted to determine if the sampled signal will be transmitted to the quantizer. Secondly, a synchronization error model is constructed to describe the master-slave synchronization system with event-triggered scheme, quantization and input saturation in a unified framework. Thirdly, on the basis of Lyapunov–Krasovskii functional, sufficient conditions for stabilization are derived which can ensure synchronization of the master system and slave system; particularly, a co-designed parameters of controller and the corresponding event-triggered parameters are obtained under the above stability condition. Lastly, two numerical examples are employed to illustrate the effectiveness of the proposed approach.     

Dual-Condition event-Triggered distributed adaptive neural control for multi-Agent systems with nonlinear fault

This paper studies the cooperative adaptive dual-condition event-triggered tracking control problem for the uncertain nonlinear nonstrict feedback multi-agent systems with nonlinear faults and unknown disturbances. Under the framework of backstepping technology, a new threshold update method is designed for the state event-triggered mechanism. At the same time, we develop a novel distributed dual-condition event-triggered strategy that combined the fixed threshold triggered mechanism acted on the controller with the new event-triggered mechanism, which can better reduce the waste of communication bandwidth. To deal with the algebraic loop problem caused by the non-affine nonlinear fault, the Butterworth low-pass filter is introduced. At the same time, the unknown function problems are solved by the neural network technology. All signals of the system are semiglobally uniformly ultimately bounded and the tracking performance is achieved, which proved by the Lyapunov stability theorem. Finally, the results of the simulation test the efficiency of the proposed control scheme.