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This article investigates the problem of delay-dependent stability for the one-area load frequency control (LFC) system with electric vehicles (EVs). Two closed-loop models of the LFC system with EVs are proposed, including the model based on the model reconstructed technique and the model with uncertain parameters that considers state of charge. By employing the Lyapunov–Krasovskii functional method, two delay-dependent stability criteria are presented for the systems under study such that a more accurate admissible delay upper bound (ADUB) can be obtained. Case studies are finally carried out to disclose the interrelationship between the ADUB, PI controller gains, and other parameters of the EVs. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of distributed cooperative longitudinal control of automated vehicle platoons subject to a variety of uncertainties, including unknown engine time lags, external disturbances, measurement noises, and actuator anomaly in follower vehicles as well as unknown leader control. First, a unified framework is proposed for accomplishing resilient vehicle platooning, which empowers longitudinal vehicle state estimation, anomaly signal estimation and compensation, and adaptive platoon controller design to be addressed in a comprehensive way. Second, a novel scalable platooning control design approach is developed to guarantee desired platoon stability and resilience over generic communication topologies and various spacing policies. A salient feature of the approach is that the design procedure does not depend on any global information of the associated topology, and thus preserves essential scalability for large and/or size-varying platoons. Third, it is shown that the proposed longitudinal platooning control approach is promising for performing flexible cooperative maneuvers such as platoon splitting and merging that are beyond the capacity of most existing longitudinal platooning strategies. Finally, simulation results for different platoon maneuvers are elaborated to substantiate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This article presents an additive-state-decomposition-based repetitive control (RC) method for a class of nonlinear systems with nonintegral-chain form and multiple mismatched disturbances. The key idea of this method is to decompose the original tracking problem for an uncertain nonlinear system into two tractable subproblems, namely RC problem for a primary linear time-invariant (LTI) periodic system and robust stabilization problem for a nonlinear secondary system. By taking the equivalent total effect of the multiple disturbances as one matched total disturbance, an improved linear extended state observer (ILESO) is constructed to estimate and compensate for the adverse effect of the multiple disturbances. The method has three significant features: First, it builds a bridge between the existing RC methods for LTI systems and nonlinear systems and, thus, broadens the application scope of RC; second, besides the known information of the model being used to the design of ILESO, the periodic nonlinearity in the plant is extracted to be treated by RC, which enhances both the transient and steady-state performances; and third, the ILESO-based control scheme and the RC law are designed separately, which is flexible for system design. The stability criterion and design procedure are presented in detail. Finally, numerical and experimental results illustrate the validity and superiorities of the method. [ABSTRACT FROM AUTHOR]

This article addresses the problem of cluster consensus for multiagent systems (MASs) associated with weighted antagonistic interactions. Compared with some existing results, a general communication topology among agents is introduced in this article, where there is no need to confine directed cycles to the root of a spanning tree. By taking into consideration the structures of directed cycles and multiple paths, the judgment of structural balance is simplified significantly. A novel cluster consensus protocol is also proposed for structurally unbalanced digraphs. Moreover, two necessary and sufficient conditions are derived, by which cluster consensus can be achieved in an MAS if and only if its communication topology contains a directed spanning tree. Then, by employing an algebra theorem, a sufficient criterion for the unstable system under a directed cycle is obtained, whether the number of agents on this cycle is odd or even. Some illustrative examples are given to demonstrate the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

This article investigates $H_{\infty }$ synchronization of delayed neural networks under a receding horizon scheme, where two types of interval time-varying delays are considered according to whether the lower bound of the delay derivative is known or not. Note that a receding horizon synchronization law can be regarded as an optimization solution at each timeslot to a minimaxization problem related closely with a certain cost functional. In this article, two cost functionals with some delay-dependent matrices are introduced, respectively, for the two types of time delays. In order to obtain less conservative conditions, a novel inequality on quadratic polynomial functions is established, which includes some existing ones as its special cases. Based on the novel inequality, two sufficient conditions are derived to design the terminal weighting matrices of the cost functionals such that the resulting synchronization error system can be stabilized with a prescribed infinite horizon $H_{\infty }$ performance level. Finally, three numerical examples are used to demonstrate the validity of the proposed results. [ABSTRACT FROM AUTHOR]

This paper is concerned with position-based synchronization of networked harmonic oscillators. Note that synchronization cannot be achieved via current-position-based protocols. The objective of this paper is to investigate the positive effects of network-induced delays on the synchronization of networked harmonic oscillators. That is, if taking network-induced delays into account, the motion of harmonic oscillators can be really synchronized via a proper position-based control protocol. In doing so, the harmonic oscillators are connected via a shared digital communication network. Different from some existing results, system measurements from oscillator nodes are sampled in an asynchronous way; and network-induced delays are assumed to be time varying and bounded, and they do not need to be synchronous with those from the other communication channels. At each oscillator node, a buffer is embedded into the controller to store the newest sampled-data packets transmitted from its neighboring nodes through communication channels. Then, based on the store of the buffer, the controller computes its control signal with its own period. As a result, the overall synchronization error system is modeled as a linear system with multiple interval time-varying delays. By employing the discretized Lyapunov–Krasovskii functional method, a sufficient condition on synchronization of networked harmonic oscillators is derived, which can ensure that the synchronization error system is asymptotically stable for network-induced delays falling into a certain closed interval whose lower bound is a positive real number. This condition is thus used to design suitable control protocols in terms of linear matrix inequalities with several tuning parameters. Finally, a multirobot platform is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Distributed coordination control is the current trend in networked systems and finds prosperous applications across a variety of fields, such as smart grids and intelligent transportation systems. One fundamental issue in coordinating and controlling a large group of distributed and networked agents is the influence of intermittent interagent interactions caused by constrained communication resources. Event-triggered communication scheduling stands out as a promising enabler to strike a balance between the desired control performance and the satisfactory resource efficiency. What distinguishes dynamic event-triggered scheduling from traditional static event-triggered scheduling is that the triggering mechanism can be dynamically adjusted over time in accordance with both available system information and additional dynamic variables. This article provides an up-to-date overview of dynamic event-triggered distributed coordination control. The motivation of dynamic event-triggered scheduling is first introduced in the context of distributed coordination control. Then some techniques of dynamic event-triggered distributed coordination control are discussed in detail. Implementation and design issues are well addressed. Furthermore, this article exemplifies two applications of dynamic event-triggered distributed coordination control in the fields of microgrids and automated vehicles. Several challenges are suggested to direct the future research. [ABSTRACT FROM AUTHOR]

This article is concerned with designing resilient state feedback controllers for a class of networked control systems under denial-of-service (DoS) attacks. The sensor samples system states periodically. The DoS attacks usually prevent those sampled signals from being transmitted through a communication network. A logic processor embedded in the controller is introduced to not only receive sampled signals but also capture information on the duration time of each DoS attack. Note that the duration time of DoS attacks is usually both lower and upper bounded. Then the closed-loop system is modeled as an aperiodic sampled-data system closely related to both lower and upper bounds of duration time of DoS attacks. By introducing a novel looped functional, which caters for the $N$ -order canonical Bessel–Legendre inequalities, some $N$ -dependent stability criteria are presented for the resultant closed-loop system. It is worth pointing out that a number of identity formulas are uncovered, which enable us to apply the notable free-weighting matrix approach to derive less conservative stability criteria. A linear-matrix-inequality-based criterion is provided to design stabilizing state-feedback controllers against DoS attacks. A satellite control system is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the network-based modeling and proportional–integral (PI) control for a continuous-time direct-drive-wheel system in a wireless network environment. The developed system can simplify configuration, reduce bus cables, and realize vehicle height adjustment. A novel network-based model is first established by constructing a PI control system and taking network-induced delays and stochastic packet dropouts into account. By using two different artificial delays to characterize the update of proportional and integral control signals, the network-based PI control system is modeled as a stochastic impulsive system with two input delays and reset equations at updating instants. Then, through involving the reset states and the relationship among two delayed states and the current state in the discontinuous Lyapunov–Krasovskii functional and actively introducing the upper bounds of nonzero network-induced delays, some exponential mean-square stability and $H_{\infty }$ performance conditions with less conservatism are derived in terms of tractable linear matrix inequalities. An algorithm is presented to determine the minimum $H_{\infty }$ performance and the corresponding PI control parameters by combining a particle swarm optimization technique with the performance condition. These results can be extended to a network-based PI control of general continuous-time linear systems. A ZigBee-based network simulation platform is finally built and some simulation results are provided to validate the proposed methods. [ABSTRACT FROM AUTHOR]

This paper presents a linear-extended-state-observer-based repetitive control (RC) method to enhance the disturbance rejection performance and tracking performance for a nonlinear system with aperiodic uncertainties and disturbances. Both design scenarios, i.e., with and without a detailed mathematical model of the plant, are considered, respectively. The proposed method exhibits the following three attractive features. First, instead of tuning the observer gain via the bandwidth idea by trial and error, available information on the plant model is used to design the observer gain and the state-feedback RC gains. As a result, the disturbance rejection ability is elevated. Second, robust stability and learning efficiency are adjusted preferentially through two tuning parameters, which effectively improve both the transient and steady-state performance. Third, the observer gain and state-feedback RC gains are simultaneously optimized through an optimization algorithm, in which an index is introduced to evaluate the overall system performance. The design procedure of the system is presented in detail. Finally, an application to tracking control of a chuck-workpiece system demonstrates the validity of the proposed method. Comparisons with the conventional RC method, the standard extended-state-observer-based RC method, and a linear active-disturbance-rejection-control-based RC method show that the proposed method can achieve the best disturbance rejection performance. [ABSTRACT FROM AUTHOR]

An event-triggered mechanism is of great efficiency in reducing unnecessary sensor samplings/transmissions and, thus, resource consumption such as sensor power and network bandwidth, which makes distributed event-triggered estimation a promising resource-aware solution for sensor network-based monitoring systems. This paper provides a survey of recent advances in distributed event-triggered estimation for dynamical systems operating over resource-constrained sensor networks. Local estimates of an unavailable state signal are calculated in a distributed and collaborative fashion based on only invoked sensor data. First, several fundamental issues associated with the design of distributed estimators are discussed in detail, such as estimator structures, communication constraints, and design methods. Second, an emphasis is laid on recent developments of distributed event-triggered estimation that has received considerable attention in the past few years. Then, the principle of an event-triggered mechanism is outlined and recent results in this subject are sorted out in accordance with different event-triggering conditions. Third, applications of distributed event-triggered estimation in practical sensor network-based monitoring systems including distributed grid-connected generation systems and target tracking systems are provided. Finally, several challenging issues worthy of further research are envisioned. [ABSTRACT FROM AUTHOR]

This paper is concerned with passivity of a class of delayed neural networks. In order to derive less conservative passivity criteria, two Lyapunov–Krasovskii functionals (LKFs) with delay-dependent matrices are introduced by taking into consideration a second-order Bessel–Legendre inequality. In one LKF, the system state vector is coupled with those vectors inherited from the second-order Bessel–Legendre inequality through delay-dependent matrices, while no such coupling of them exists in the other LKF. These two LKFs are referred to as the coupled LKF and the noncoupled LKF, respectively. A number of delay-dependent passivity criteria are derived by employing a convex approach and a nonconvex approach to deal with the square of the time-varying delay appearing in the derivative of the LKF. Through numerical simulation, it is found that: 1) the coupled LKF is more beneficial than the noncoupled LKF for reducing the conservatism of the obtained passivity criteria and 2) the passivity criteria using the convex approach can deliver larger delay upper bounds than those using the nonconvex approach. [ABSTRACT FROM AUTHOR]

This paper is concerned with active power sharing and frequency regulation in an islanded microgrid under event-triggered communication. A distributed secondary control scheme with a sampled-data-based event-triggered communication mechanism is proposed to achieve active power sharing and frequency regulation in a unified framework, where neighborhood sampled-data exchange occurs only when the predefined triggering condition is violated. Compared with traditional periodic communication mechanisms, the proposed event-triggered communication mechanism shows some prominent ability in reducing the number of communication among neighbors while guaranteeing the desired performance level of microgirds. By employing the Lyapunov–Kravovskii functional method, some sufficient conditions are derived to characterize the effects of control gains, system parameters, and sampling period on stability of microgrids. Finally, case studies on a modified IEEE 34-bus test system are conducted to evaluate the performance of the proposed distributed control scheme, showcasing its effectiveness, robustness against load changes, and plug-and-play ability. [ABSTRACT FROM AUTHOR]

This paper is concerned with energy-to-peak state estimation on static neural networks (SNNs) with interval time-varying delays. The objective is to design suitable delay-dependent state estimators such that the peak value of the estimation error state can be minimized for all disturbances with bounded energy. Note that the Lyapunov–Krasovskii functional (LKF) method plus proper integral inequalities provides a powerful tool in stability analysis and state estimation of delayed NNs. The main contribution of this paper lies in three points: 1) the relationship between two integral inequalities based on orthogonal and nonorthogonal polynomial sequences is disclosed. It is proven that the second-order Bessel–Legendre inequality (BLI), which is based on an orthogonal polynomial sequence, outperforms the second-order integral inequality recently established based on a nonorthogonal polynomial sequence; 2) the LKF method together with the second-order BLI is employed to derive some novel sufficient conditions such that the resulting estimation error system is globally asymptotically stable with desirable energy-to-peak performance, in which two types of time-varying delays are considered, allowing its derivative information is partly known or totally unknown; and 3) a linear-matrix-inequality-based approach is presented to design energy-to-peak state estimators for SNNs with two types of time-varying delays, whose efficiency is demonstrated via two widely studied numerical examples. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of robust ${H}_{\infty}$ control of an uncertain discrete-time Takagi–Sugeno fuzzy system with an interval-like time-varying delay. A novel finite-sum inequality-based method is proposed to provide a tighter estimation on the forward difference of certain Lyapunov functional, leading to a less conservative result. First, an auxiliary vector function is used to establish two finite-sum inequalities, which can produce tighter bounds for the finite-sum terms appearing in the forward difference of the Lyapunov functional. Second, a matrix-based quadratic convex approach is employed to equivalently convert the original matrix inequality including a quadratic polynomial on the time-varying delay into two boundary matrix inequalities, which delivers a less conservative bounded real lemma (BRL) for the resultant closed-loop system. Third, based on the BRL, a novel sufficient condition on the existence of suitable robust ${H}_{\infty}$ fuzzy controllers is derived. Finally, two numerical examples and a computer-simulated truck-trailer system are provided to show the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Fixed-time cooperative control is currently a hot research topic in multiagent systems since it can provide a guaranteed settling time, which does not depend on initial conditions. Compared with asymptotic cooperative control algorithms, fixed-time cooperative control algorithms can achieve better closed-loop performance and disturbance rejection properties. Different from finite-time control, fixed-time cooperative control produces the faster rate of convergence and provides an explicit estimation of the settling time independent of initial conditions, which is desirable for multiagent systems. This paper aims at presenting an overview of recent advances in fixed-time cooperative control of multiagent systems. Some fundamental concepts about finite- and fixed-time stability and stabilization are first recalled with insight understanding. Then, recent results in finite- and fixed-time cooperative control are reviewed in detail and categorized according to different agent dynamics. Finally, this paper raises several challenging issues that need to be addressed in the near future. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of cluster formation control for a networked multi-agent system (MAS) in the simultaneous presence of aperiodic sampling and communication delays. First, to fulfill multiple formation tasks, a group of agents are decomposed into $M$ distinct and nonoverlapping clusters. The agents in each cluster are then driven to achieve a desired formation, whereas the MAS as a whole accomplishes $ M $ cluster formations. Second, by a proper modeling of aperiodic sampling and communication delays, an aperiodic sampled-data cluster formation protocol (CFP) is delicately constructed such that the information exchanges among neighboring agents only occur intermittently at discrete instants of time. Third, a detailed theoretical analysis of cluster formability is carried out and a sufficient and necessary condition is provided such that the system is $M$-cluster formable. Furthermore, a discontinuous Lyapunov functional approach is developed to derive a design criterion on the existence of an admissible sampled-data CFP. Finally, numerical simulations on a team of nonholonomic mobile robots are given to illustrate the effectiveness of the obtained theoretical result. [ABSTRACT FROM AUTHOR]

Event-triggered consensus of multiagent systems (MASs) has attracted tremendous attention from both theoretical and practical perspectives due to the fact that it enables all agents eventually to reach an agreement upon a common quantity of interest while significantly alleviating utilization of communication and computation resources. This paper aims to provide an overview of recent advances in event-triggered consensus of MASs. First, a basic framework of multiagent event-triggered operational mechanisms is established. Second, representative results and methodologies reported in the literature are reviewed and some in-depth analysis is made on several event-triggered schemes, including event-based sampling schemes, model-based event-triggered schemes, sampled-data-based event-triggered schemes, and self-triggered sampling schemes. Third, two examples are outlined to show applicability of event-triggered consensus in power sharing of microgrids and formation control of multirobot systems, respectively. Finally, some challenging issues on event-triggered consensus are proposed for future research. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the state estimation for neural networks with two additive time-varying delay components. Three cases of these two time-varying delays are fully considered: 1) both delays are differentiable uniformly bounded with delay-derivative bounded by some constants; 2) one delay is continuous uniformly bounded while the other is differentiable uniformly bounded with delay-derivative bounded by certain constants; and 3) both delays are continuous uniformly bounded. First, an extended reciprocally convex inequality is introduced to bound reciprocally convex combinations appearing in the derivative of some Lyapunov–Krasovskii functional. Second, sufficient conditions are derived based on the extended inequality for three cases of time-varying delays, respectively. Third, a linear-matrix-inequality-based approach with two tuning parameters is proposed to design desired Luenberger estimators such that the error system is globally asymptotically stable. This approach is then applied to state estimation on neural networks with a single interval time-varying delay. Finally, two numerical examples are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked systems. Compared with some existing event-triggered and self-triggered schemes, a sampled-data-based event-triggered scheme can ensure a positive minimum inter-event time and make it possible to jointly design suitable feedback controllers and event-triggered threshold parameters. Thus, more attention has been paid to the sampled-data-based event-triggered scheme. A deep investigation is first made on the sampled-data-based event-triggered scheme. Then, recent results on sampled-data-based event-triggered state feedback control, dynamic output feedback control, $H_\infty$ filtering for networked systems are surveyed and analyzed. An overview on sampled-data-based event-triggered consensus for distributed multiagent systems is given. Finally, some challenging issues are addressed to direct the future research. [ABSTRACT FROM PUBLISHER]

This paper is concerned with decentralized event-triggered dissipative control for systems with the entries of the system outputs having different physical properties. Depending on these different physical properties, the entries of the system outputs are grouped into multiple nodes. A number of sensors are used to sample the signals from different nodes. A decentralized event-triggering scheme is introduced to select those necessary sampled-data packets to be transmitted so that communication resources can be saved significantly while preserving the prescribed closed-loop performance. First, in order to organize the decentralized data packets transmitted from the sensor nodes, a data packet processor (DPP) is used to generate a new signal to be held by the zero-order-hold once the signal stored by the DPP is updated at some time instant. Second, under the mechanism of the DPP, the resulting closed-loop system is modeled as a linear system with an interval time-varying delay. A sufficient condition is derived such that the closed-loop system is asymptotically stable and strictly (Q0,S0,R0) -dissipative, where Q0,S0 , and R0 are real matrices of appropriate dimensions with Q0 and R0 symmetric. Third, suitable output-based controllers can be designed based on solutions to a set of a linear matrix inequality. Finally, two examples are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Networked control systems (NCSs) are systems whose control loops are closed through communication networks such that both control signals and feedback signals can be exchanged among system components (sensors, controllers, actuators, and so on). NCSs have a broad range of applications in areas such as industrial control and signal processing. This survey provides an overview on the theoretical development of NCSs. In-depth analysis and discussion is made on sampled-data control, networked control, and event-triggered control. More specifically, existing research methods on NCSs are summarized. Furthermore, as an active research topic, network-based filtering is reviewed briefly. Finally, some challenging problems are presented to direct the future research. [ABSTRACT FROM PUBLISHER]