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• In this paper, double closed-loop framework is proposed with the functions of faults and cyber-attacks detection. • The models of cyber-attacks, denial-of-service, information disclosure (privacy attack), stealthy attack and replay attacks, are formulated to be typical NCS models with parameter uncertainties from control theory perspective. • Information technique (IT) is synthesized together with control theory, and a novel framework is designed based on typical CPS structure, effective attack defense scenarios is devised and applied on this framework to detect and identify the cyber-attacks. In this paper, the issue of CPS security is investigated. By analyzing the process of multi-sources cyber-attacks of denial-of-service (DoS), information disclosure, stealthy attack and replay attack, a unified system model with uncertainties is formulated. Under this system model framework, robust control theory is applied to design the control scenarios for cyber-attack prevention. Furthermore, a double closed-loop NCS framework combined with information integration technology is proposed, necessary conditions for security guarantee are derived. Finally, a DC motor speed moderating example is given to demonstrate the problem. [ABSTRACT FROM AUTHOR]

This paper focuses on the optimal coordination control problem for continuous-time nonlinear multi-agent systems with completely unknown dynamics via a data-based distributed adaptive dynamic programming method. As for most real-world applications, accurate system models are complicated to obtain, which restricts the application of the conventional methods. Moreover, it is challenging to design optimal coordination control of multi-agent systems especially for the time-varying communication topology. To deal with the difficulties, we investigate a distributed adaptive dynamic programming method with identifier-critic architecture under the switching communication topology. First, using the available system data, an online adaptive identifier is developed to approximate the unknown model dynamics, and simultaneously a critic neural network is employed for approximation of the optimal cost function, which yields approximated optimal coordination control in real time. Then, we analyze the stability of our proposed scheme. Eventually, the simulation illustrates the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

Integrating wireless networks in control systems allow users to take benefit from modular and flexible system design, but the analysis and design of such systems pose new challenges such as more serious packet loss. This study develops a new multi-instant switching controller of nonlinear networked systems under unreliable wireless digital channels. The proposed controller can be viewed as an improvement of previous results concerned with the homogenous polynomials approach, since it presents a denser subdivision of the joint space of multi-instant normalized membership functions and therefore essentially yields an efficient multi-instant switching mechanism for the first time. As a result, more efficient results can be obtained in the study. Finally, an illustrative example is provided to demonstrate the effectiveness of the multi-instant switching controller. [ABSTRACT FROM AUTHOR]

This study investigates the problem of tracking control of nonlinear fuzzy systems with a limited network communication. A new adaptive event-triggered data transmission scheme is proposed to save the limited network bandwidth. The threshold of event-triggered condition has a great influence on the rate of data releasing. Different from the conventional method by presetting the threshold as a fixed value, the threshold, in this study, is regulated by the error state of nonlinear systems and the reference model adaptively, which denotes that the rate of data releasing is followed by the external variation. By constructing a proper Lyapunov function with consideration of the proposed adaptive event-triggering condition, an off-line co-design method to achieve the fuzzy controller gains and the parameters of event-triggering condition is developed. An example of Duffing forced-oscillation system with the limited network communication tracking the states of linear reference model is applied to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed event-triggered cooperative control for multiple photovoltaic (PV) generators in distribution power system. Considering the issue of limited bandwidth of communication network in practical application, two types of novel distributed event-triggered mechanism are introduced to reduce the information transmission pressure, and the distributed cooperative controllers are designed for PV generators based on the proposed triggering schemes. Under the control strategy, the fair utilization of all PV generators is realized, and the active power flow across certain transmission line and the voltage of critical bus can be restored. Simulation results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The problem of relaxed observer design for discrete-time Takagi–Sugeno (T–S) fuzzy systems is addressed in this paper. With the framework of improved homogenous matrix polynomials, a novel kind of slack variable approach, which is homogenous polynomially parameter-dependent on multi-instant normalized fuzzy weighting functions with arbitrary degrees, is proposed by developing an efficient multi-instant augmented multi-indexed matrix approach. Since the algebraic properties of multi-instant normalized fuzzy weighting functions are collected into a set of augmented multi-indexed matrices, more information about multi-instant normalized fuzzy weighting functions can be involved into observer design. As a result, the relaxation quality of fuzzy observer design can be significantly improved. Finally, two numerical examples are given to illustrate the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

A decentralized adaptive neural output feedback control scheme is presented for a class of large-scale time-delay systems with saturating inputs. The observer is constructed to estimate the immeasurable states of the system and the auxiliary system is designed to compensate the nonsmooth nonlinearities of input saturation constraints. Also, the control strategy is developed by the backstepping recursive method combining with neural networks (NNs) for the approximation of the unknown functions and dynamic surface control (DSC) technique for the well known ‘explosion of complexity’ problem. The advantage of this scheme is that it only relies on the output information of the system and there is no requirement for exact priori knowledge about the system parameters. It is proved that the control approach guarantees all signals in the closed-loop system uniformly ultimately bounded. Simulation results are provided to demonstrate the effectiveness and usefulness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Abstract: This paper is concerned with the event-based fault detection for the networked systems with communication delay and nonlinear perturbation. We propose an event-triggered scheme, which has some advantages over existing ones. The sensor data is transmitted only when the specified event condition involving the sampled measurements of the plant is violated. An event-based fault detection model is firstly constructed by taking the effect of event-triggered scheme and the network transmission delay into consideration. The main purpose of this paper is to design an event-based fault detection filter such that, for all unknown input, communication delay and nonlinear perturbation, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions for the existence of the desired fault detection filter are established in terms of linear matrix inequalities. Based on these conditions, the explicit expression is given for the designed fault detection filter parameters. A numerical example is employed to illustrate the advantage of the introduced event-triggered scheme and the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: This paper investigates robust controller design for Markovian jump systems (MJSs) with partially known transition probabilities (TPs) and nonlinearities. A general nonlinearity model is proposed, the generalization lies in three aspects: (1) the nonlinearities include both state and delayed state information; (2) the nonlinearities satisfy sector-bounded conditions; (3) apart from the lower and upper bounds, the probability information of the nonlinearities belonging to different sector bounds is utilized. The MJSs are considered with some of the TPs completely unknown, which can cover the MJSs with completely known TPs and completely unknown TPs as special cases. It should be noted that the relationship between known and unknown TPs is utilized, which can reduce the conservatism of the results. By using the Lyapunov functional method, sufficient conditions are derived. At last, two simulation examples show the application and effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the consensus problem of a set of discrete-time heterogeneous multi-agent systems with random communication delays represented by a Markov chain, where the multi-agent systems are composed of two kinds of agents differed by their dynamics. First, distributed consensus control is designed by employing the event-triggered communication technique, which can lead to a significant reduction of the information communication burden in the multi-agent network. Then, the mean square stability of the closed loop multi-agent systems is analyzed based on the Lyapunov functional method and the Kronecker product technique. Sufficient conditions are obtained to guarantee the consensus in terms of linear matrix inequalities (LMIs). Finally, a simulation example is given to illustrate the effectiveness of the developed theory. [Copyright &y& Elsevier]

Abstract: This paper investigates the consensus problem for a set of discrete-time heterogeneous multi-agent systems composed of two kinds of agents differed by their dynamics. The consensus control is designed based on the event-triggered communication scheme, which can lead to a significant reduction of the information communication burden in the multi-agent network. Meanwhile, only the communication between the agent and its local neighbors is needed, therefore, the designed control is essentially distributed. Based on the Lyapunov functional method and the Kronecker product technique, a sufficient condition is obtained to guarantee the consensus of heterogeneous multi-agent systems in terms of linear matrix inequality (LMI). Simulation results illustrate the effectiveness of the developed theory in the last. [Copyright &y& Elsevier]

Abstract: This paper studies the problem of fault tolerant control design for time-delayed systems subject to actuator saturation. Delay- and fault-range-dependent estimate for the domain of attraction of the origin is presented using the linear matrix inequalities (LMIs) techniques. An illustrative example is exploited to show the effectiveness of the proposed design procedures. [Copyright &y& Elsevier]

Abstract: This paper concerns the control design for networked control systems assuming that network conditions are time-varying or even vary randomly. A novel state feedback control with the compensator for the effects of network delays in both forward and feedback channels is proposed by introducing an augmented state variable. Criteria for the design of the feedback gain are derived under the assumption that network delays are time-varying with knowing the variation interval only or the distribution probabilities and the parameter matrices are of polytopic-type. Simulation study shows the effectiveness of the proposed scheme and also provides comparison results between the proposed controllers under different assumption on the network delays. [Copyright &y& Elsevier]

Abstract: This paper considers the design problem of delay-dependent robust control for interval time-delay systems (ITDS). Based on the Lyapunov–Krasovskii functional approach and the convexity of the matrix equations, a delay-dependent bounded real lemma (BRL) is firstly proposed, which is shown in terms of linear matrix inequalities. Then by applying the BRL, sufficient conditions can be obtained for the asymptotic stabilizability of the uncertain ITDS with a prescribed performance index. Finally, numerical examples are provided to illustrate the less conservativeness of the proposed methods than some existing results. [Copyright &y& Elsevier]

Abstract: In this paper, the reliable control design is considered for networked control systems (NCSs) against probabilistic actuator fault with different failure rates, measurements distortion, random network-induced delay and packet dropout. A new distribution-based fault model is proposed, which also contains the probability distribution information of the random delay and packet dropout. By using Lyapunov functional and new technique in dealing with time delay, stability and stabilization criteria are derived in terms of linear matrix inequalities. The provided numerical example and vertical takeoff and landing (VTOL) aircraft system illustrate that: firstly, using the distribution information of the delay, the maximum effective delay bound (MEDB) can be greatly improved, secondly, the proposed reliable controller can stabilize the NCSs with probabilistic actuator fault and measurements distortion, which may be unstable under the controller designed without considering the unreliable cases. [ABSTRACT FROM AUTHOR]

Abstract: Communication delays in networked control systems (NCSs) has been shown to have non-uniform distribution and multifractal nature. This paper proposes a delay distribution based stability analysis and synthesis approach for NCSs with non-uniform distribution characteristics of network communication delays. A stochastic control model related with the characteristics of communication networks is established to describe the NCSs. Then, delay distribution-dependent NCS stability criteria are derived in the form of linear matrix inequalities (LMIs). Also, the maximum allowable upper delay bound and controller feedback gain can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples showed that the results derived from the proposed method are less conservativeness than those derived from the existing methods. [Copyright &y& Elsevier]

At present, the hierarchical control strategy which includes cyber and physical layers is one of the most widely used control strategies in networked direct current microgrid. In general, through the controller and actuator, the communication data in cyber layer can be used to accomplish the control missions in physical layer, e.g. achieving stable operation or economic operation etc. However, when actuator fault occurs in communication, the normal operation of cyber layer will be affected. Thus, the control effect of physical layer will be also affected. Considering with the above problems, a hierarchical control strategy based on adaptive dynamic program and event-triggered consensus algorithms is proposed to realize the economic operation of microgrid. In this strategy, the main designs are as follows: 1. To deal with the actuator fault problem in the process of consensus control, the fault observer and adaptive dynamic program-based controller are designed in the cyber layer; 2. Also in the cyber layer, an event-triggered consensus algorithm is proposed to adjust distributed energy resources to output their optimal power and make microgrid run economically; 3. To maintain the voltage stable while the power is adjusted, a secondary control strategy is proposed in the physical layer. Finally, the experimental results have verified the effectiveness of the designed strategies. [ABSTRACT FROM AUTHOR]

The problem of relaxed state estimation of a class of discrete-time nonlinear plants is studied by developing an improved fuzzy partition-based switching observer. By introducing a pair of weighted scalars, the whole interval spanned by all the normalized fuzzy weighting functions at the present sampling instant is delimited as some non-overlapping sub-intervals. Then, an available fuzzy switching observer can be designed with all kinds of possible switching modes. Because much more information for each partition sub-interval could be considered in its activated switching mode, the obtained method can be less conservative than the existing methods reported in recent references. Finally, two illustrative simulations are given for testing the superiority of the proposed method over previous ones. [ABSTRACT FROM AUTHOR]

The problem of robust fault estimation of discrete-time nonlinear plant is investigated from the view of reducing its conservatism and restraining its on-line computational burden simultaneously. Firstly, an enhanced maximum-priority-based switching law is developed for subdividing the distribution types of normalized fuzzy weighting functions in a more flexible way. Then, a new fuzzy fault estimation observer is proposed with different switching modes in accordance with the updated value of the above switching law. More importantly, the proposed designing criterion is further optimized by considering the balance between reducing the conservatism and restraining the on-line computational burden. Finally, a set of simulation comparisons over the previous ones are provided to illustrate the advantages of our method developed in this paper. [ABSTRACT FROM AUTHOR]

An adaptive neural network control strategy and its event-triggered controller are designed for non-affine pure-feedback uncertain systems based on nonlinear gains and recursive sliding-mode dynamic surfaces. A kind of nonlinear gain functions is introduced into the traditional framework of dynamic surface control (DSC) with recursive sliding-mode to make a compromise between control accuracy and transient performance. Radial basis function (RBF) neural networks (NNs) are adopted to approximate unknown functions at each step, and novel adaptive update laws with leakage terms of σ -modification is constructed. To reduce the action number of the actuator, an extended control strategy in an event-triggered manner is proposed. By the Lyapunov function, it is proven that both of the two control strategies can force the tracking error arbitrarily small and guarantee all the signals in the closed-loop system uniformly ultimately bounded. Finally, simulation results are provided to verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

• A consensus-based primary control (CBPC) is designed to optimize the economic benefit of MG. • The method of path planning and reconstruction is designed to optimize the communication cost. • A cyber-physical vulnerability assessment method is proposed. • A consensus-based secondary control (CBSC) method is proposed to accomplish the secondary control on output voltages of DERs. In the islanded microgrid (MG), to improve the control effect of the output voltages of DERs and keep the economical operation of MG, a consensus-based economic hierarchical control strategy is proposed in this paper. The corresponding control structure is divided into physical and cyber layers, where the cyber layer is mainly composed by communicators. In these two layers, there are two main designs: the consensus-based primary control (CBPC) method and the secondary control (CBSC) method. In CBPC: Firstly, the undirected communication path among communicators is designed by path planning. Then, based on the constructed path, an economic P–U droop control method considering with line loss and flexible load is realized by using consensus control. In CBSC: Firstly, a cyber-physical vulnerability assessment method is designed. Based on this method, the DER with the lowest vulnerability is selected to be connected with the "virtual leader". And when the data transmission behavior of the undirected communication path is selected, the undirected network can be transferred as a directed network. Thus, it can make the virtual leader-following consensus control (VLFCC) and the secondary control on voltage accomplished. Finally, the simulation results show the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this paper, we focus on an output secure consensus control issue for nonlinear multi-agent systems (MASs) under sensor and actuator attacks. Followers in an MAS are in strict-feedback form with unknown control directions and unknown dead-zone input, where both sensors and nonlinear characteristics of dead-zone in actuators are paralyzed by malicious attacks. To deal with sensor attacks, uncertain dynamics in individual follower are separated by a separation theorem, and estimation parameters are introduced for compensating and mitigating the influence from adversaries. The influence from actuator attacks are treated as a total displacement in a dead-zone nonlinearity, and an upper bound, as well as its estimation, is introduced for this displacement. The dead-zone nonlinearity, sensor attacks and unknown control gains are gathered together regarded as composite unknown control directions, and Nussbaum functions are utilized to address the issue of unknown control directions. A distributed secure consensus control strategy is thus developed recursively for each follower in the framework of surface control method. Theoretically, the stability of the closed-loop MAS is analyzed, and it is proved that the MAS achieves output consensus in spite of nonlinear dynamics and malicious attacks. Finally, theoretical results are verified via a numerical example and a group of electromechanical systems. [ABSTRACT FROM AUTHOR]

Abstract To achieve the frequency restoration (FR) and accurate reactive power sharing (RPS) in islanded microgrids (MGs), an improved P-f droop control is proposed. Firstly, the inverter impedance, whose value is set by the virtual impedance method, is used to minimize the impact of line resistance on powers coupling and RPS. Then, in order to restore the frequency of distributed generations (DGs) to the rated value, the reference is changed for compensating the frequency deviation (FD) caused by loads change. And the fast FR rate is achieved under a large constant k. Besides, in order to eliminate the inaccuracy of RPS caused by voltages difference (VD), the line voltage drop (LVD) is used to compensate the voltage droop characteristics. The use of voltage feedback ensures that the obtained voltage is desired after the LVD compensation. Finally, the simulation in RT-LAB indicates the effectiveness of proposed method in an islanded MG model. [ABSTRACT FROM AUTHOR]

Abstract We address the leader-following tracking consensus issue for a class of linear multi-agent systems (MASs) via dynamic event-triggered (DET) approaches in this paper. The DET communication mechanism is introduced by an additional internal dynamic variable, and is developed to schedule agents' data transmission. State observers are also employed to tackle the scenario wherein inner information of follower agents are not available for measurement. And then, state-based and observer-based distributed control proposals are proposed on the basis of dynamic event-triggered mechanism (DETM), respectively. To avoid continuous measurement information monitor, we present a technical approach for generation of the combinational information from their own neighboring agents only at event instants. The stabilities of the resulting closed-loop systems, both state-feedback one and output-feedback one, are rigorously analyzed in theory, and it is proven that all signals in the closed-loop system are bounded and Zeno behavior is also excluded. Simulation examples are presented to illustrate the theoretical claims. [ABSTRACT FROM AUTHOR]

An event-trigger-based adaptive output feedback approximately optimal tracking control strategy is presented for a class of multiple-input multiple-output (MIMO) non-affine nonlinear systems. A fuzzy state observer is designed for estimation of internal states, where fuzzy logic systems (FLSs) are employed to approximate unknown nonlinear dynamics. In the event-triggered and backstepping control framework, an output feedback control strategy, consisting of the adaptive backstepping control and the approximately optimal control via the adaptive dynamic programming (ADP) method, is presented. This strategy not only reduces the number of executions from the actuator but also guarantees that the performance index of the system is approximately minimized. Finally, two simulation examples are provided to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]