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In this article, the problems of inverse-optimal consensus control (IOCC) for single-integral dynamics in Caputo continuous-time and Grunwald–Letnikov (G-L) discrete-time fractional-order multiagent systems (FOMASs) are investigated. For continuous-time FOMASs, by virtue of the variational method, the optimal solution under the constraint of the global performance index function is presented, and then the optimal state-feedback gain matrix (OSFGM) is derived through the Laplace transform and the inverse transform of fractional order. For discrete-time FOMASs, the OSFGM based on the algebraic Riccati equation (ARE) is computed, then it is shown that the OSFGM is a (asymmetric) Laplace matrix which has a zero eigenvalue and the corresponding network structure is a complete graph. Moreover, we rigorously prove that consensus can be achieved under the optimal state-feedback gain matrices. Finally, two simulation examples are shown to check the validity of the proposed theorems. [ABSTRACT FROM AUTHOR]

In this article, we study the consensus issues of multiagent systems (MASs) without any information of the system model by using the reinforcement learning (RL) method and event-based control strategy. First, we design an adaptive event-based consensus control protocol using the local sampled state information so that the consensus errors of all agents are uniformly ultimately bounded. The validity of the above event-triggered adaptive control protocol is confirmed by excluding the Zeno behavior within finite time. Then, based on the RL approach, we present a model-free algorithm to get the feedback gain matrix, and accomplish constructing the adaptive event-triggered control strategy without the knowledge of model information. Distinct with the existing related works, this RL-based event-triggered adaptive control algorithm only relies on the local sampled state information, irrelevant to any model information or global network information. Finally, we provide some examples to demonstrate the validity of the above adaptive event-based consensus algorithm. [ABSTRACT FROM AUTHOR]

This article studies the consensus control problem of second-order multiagent systems with switching dynamics, which consist of a continuous-time and a discrete-time subsystem. A novel control protocol is proposed for fixed digraphs by using the same control strategy for two subsystems so that the controller can keep the control strategy unchanged when systems switch. Moreover, this control strategy uses only sampled position data at the current sampling time and the previous sampling time to deal with this possible situation when speed information is difficult to be measured, which is also robustness and low cost. Some necessary and sufficient conditions to achieve consensus are derived about the network topology, structure and sampling period. At last, a few simulation examples are given. [ABSTRACT FROM AUTHOR]

A consensus control issue is studied for general second-order multiagent systems via Q-learning method in this article. A novel second-order type with discrete-time dynamics is investigated to solve the corresponding consensus issues. Under fixed directed topology, in order to achieve general second-order consensus for the systems, a model-free Q-learning method is proposed, which can derive the coupling gains matrix without any information from the system dynamics. Moreover, applying the obtained coupling gains matrix, this general second-order multiagent systems can achieve consensus. Then, for undirected graphs, a similar corollary is obtained for this system to achieve general second-order consensus by means of the Q-learning method. Finally, the correctness of the new method is confirmed by several simulation examples. [ABSTRACT FROM AUTHOR]

In this article, we propose two model-free algorithms using state or output feedback for saturated discrete-time multiagent systems (SDTMASs) to attain global containment control. In most previous works, the control input can avoid saturation by utilizing the low gain feedback (LGF) method whereas requiring the knowledge of agent dynamics, and SDTMASs just can attain semi-global containment control. Distinct with the previous works, first, based on the $Q$ -learning (QL) technique, this article defines a $Q$ -function and deduces the corresponding QL Bellman equation, which is the most important part of the QL algorithm. Then, in order to solve the QL Bellman equation, we propose two iterative model-free algorithms using state and output feedback, and the LGF matrix can be acquired from that solution directly. Furthermore, under the state and output feedback control protocols with the feedback matrices obtained from the proposed model-free algorithms, the SDTMASs can achieve global containment control instead of semi-global containment control. Finally, we present some simulations to confirm the validity of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This article studies the flocking problem of multiagent systems (MASs) with a dynamic virtual leader (VL) for the linear systems subject to time-varying uncertainties and external disturbance problems. We assume that the agents follow a leader with a bounded acceleration, which information is sensed only by the informed agents. We assign an adaptive estimator to each uninformed agent to estimate the velocity of the leader. By deriving a lemma and using a standard adaptive law, we design a continuous adaptive controller for solving the problem under the mentioned challenges, which is also fully distributed. The designed flocking control ensures that the velocity of followers asymptotically is converged to that of the VL. Also, the agents’ network remains connected, and no collision occurs among agents. Finally, we present a simulation that illustrates the validity of the results. [ABSTRACT FROM AUTHOR]

In this paper, the leader–follower robust synchronization issue is mainly addressed for reaction–diffusion neural networks (RDNNs) with multiple leaders and external disturbances under directed graphs. Based on the σ modification approach, we propose a novel distributed adaptive controller by adding a term − θ i (c i − 1) 2 to avoid the phenomenon of parameter drift, that is, the adaptive parameters grow to infinity. Meanwhile, different from the adaptive control algorithm proposed in the undirected graph, we introduce a new function χ i (t) to provide additional freedom for the design to achieve robust containment when confronted with external disturbances. Further, the robustness of tracking synchronization with one leader is guaranteed by the proposed adaptive controller when the external disturbances concerning L 2 norm are bounded. Finally, relevant numerical simulation graphics are displayed separately to verify the correctness of the related theoretical results. [ABSTRACT FROM AUTHOR]

This essay considers the bipartite consensus of matrix-weighted second-order multi-agent systems with structurally unbalanced antagonistic interactions networks. Owing to the influence of matrix-weights, bipartite consensus and cluster bipartite consensus can also be reached, which is different from the existing works on signed networks. With the assistance of Lyapunov stability and matrix-valued Gauge transformation, a condition to achieve bipartite consensus is established. Moreover, a relatively straightforward algebraic graph condition for reaching cluster bipartite consensus is attained. Finally, simulation examples are supplied to illustrate the obtained results. • The bipartite consensus of MASs is investigated for structurally unbalanced matrix-weighted signed networks. • The MASs can be reached bipartite consensus and cluster bipartite consensus. • All the clusters can be obtained by designing matrix weights. [ABSTRACT FROM AUTHOR]

The containment control problem in fractional-order multiagent systems over a directed graph is studied in this article. Two distributed control protocols with or without time delays are designed by utilizing the sampled position and velocity data. Then, based on the knowledge of the matrix theory and Laplace transform, some necessary and sufficient conditions to reach containment are derived. For the protocol with time delays, similar sufficient and necessary conditions are obtained. Finally, some simulation examples are designed to verify that the theorems are correct. [ABSTRACT FROM AUTHOR]

This article investigates the observer-based non-negative scaled edge-consensus problems of a continues-time networked system with or without input saturation, in which the proposed algorithm only uses the neighboring edges’ outputs. First, the original networked model and preliminary algorithm are simplified by using the line graph theory and constructing a new variable. Then the specific mathematical formulations of feedback matrix and observer matrix are both derived by combining $H_{\infty }$ control theory and low-gain feedback technique. Next, sufficient conditions which can guarantee the non-negative edge states and bounded control inputs are obtained. Moreover, the advantages of low-gain feedback technique for guaranteeing the non-negative edge states and designing the algorithm are developed. Finally, three cases are used to verify the validity of the theorems. [ABSTRACT FROM AUTHOR]

This article studies the consensus of hybrid second-order multiagent systems (MASs), where the hybrid MAS is constituted by the continuous-time second-order (CTSO) and discrete-time second-order (DTSO) dynamic agents. First, a hybrid consensus algorithm is proposed, where a sample-data control is considered in the CTSO subsystems. Under the proposed hybrid consensus algorithm, the convergence of the hybrid second-order MAS matrix is analyzed. Second, a sufficient and necessary condition is proposed, which indicates that the controller parameters, such as coupling gains and the sampling interval, and eigenvalues of network topology have a significant impact on the system consensus. Finally, several simulation examples are presented to prove the validity of the results. [ABSTRACT FROM AUTHOR]

In this article, by using the linear graph theory, modified algebraic Riccati equation (MARE)-based method and duality principle, two interaction protocols are proposed to achieve the scaled edge-consensus of networked discrete-time systems with unmeasurable edge-sates. Meanwhile, drawing support from MARE-based low-gain feedback technique and positive system theory, sufficient conditions are derived to ensure the bounded control inputs and positive edge-states. Moreover, feedback matrices and observer matrices are, respectively, constructed by utilizing the solutions of MARE and modified algebraic dual Riccati equation (MADRE). Remarkably, the theoretical results only use the edge number and vertex number of network rather than the global information of network. Finally, five examples are shown to demonstrate the feasibility of the interaction protocols. [ABSTRACT FROM AUTHOR]

This paper studies second-order consensus problem on the matrix-weighted undirected network, which is a generalization of second-order scalar-weighted network. The matrix coupling can describe the interdependencies of multi-dimensional states among agents. To highlight the influence of matrix coupling, we analyze the double integral model in matrix-weighted multiagent system network. A sufficient and necessary algebraic condition based on coupling strength, matrix theory and Lyapunov stability theory is established to achieve second-order consensus. With aid of the established property, a fairly straightforward algebraic graph condition is obtained, which ensures that the matrix-weighted multiagent system achieves second-order consensus. Moreover, owing to the existence of positive semi-definite connections, the clustering phenomena naturally exists, which shows that matrix coupling plays an important role in the convergence of the matrix-weighted multiagent system network. And an algebraic graph condition for finding all clusters is offered, which can guarantee the desired number of clusters via designing matrix-weights in practical applications. Finally, four simulation examples are given to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper studies the consensus in fractional-order multiagent systems over directed graph via sampled-data control method. A distributed control protocol using the sampled position and velocity data is designed. By virtue of the Mittag-Leffler function, Laplace transform, and matrix theory, some necessary and sufficient conditions associated with the sampling period, the fractional order, the coupling strengths, and the network structure to obtain consensus of the systems are obtained. Then, some detailed discussions are presented about how to select the sampling period and how to design the coupling strengths to attain the consensus of the systems, respectively. Lastly, some numerical simulation results are illustrated to reflect the availability of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Generally, nature is understood and explored from the point of view of integer order, however, lots of physical systems in complex practical environments can exhibit the fractional-order (non-integer order) dynamics, which can better reveal the essential properties, behaviors and the law of basic development. A novel fractional-order model with time-delay is built and the fractional-order controllability problem of networked multi-agent systems (MASs) is discussed. Comparing with the integer-order controllability problem for MASs, the fractional-order controllability problem of MASs not only needs to consider the dynamics of the agent itself, the communication and connection between the agents and the protocols followed by the evolution of the agent undefined state, but also to consider the order number of MASs. It is also shown that the fractional-order controllability of MASs with time-delay only lies on the communication interaction from the leaders to followers and the order number of such system, but time-delay has no effect on the controllability via the controllable rank criterion. Some computationally efficient conditions of the fractional-order controllability for MASs with time-delay are obtained based on fixed and switching topologies, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the formation containment control under sampling and with time delays for multi-agent systems (MASs). First, a novel sampling control protocol for the MASs to achieve formation containment is proposed, where the communication among agents is only occurred at the sampling instance. Then the communication load and the waste of energy can be decreased significantly. In addition, time delays are considered in this paper. Second, by establishing an appropriate Lyapunov function, sufficient conditions for MASs with sampled data and time delays reaching formation containment are obtained by handling the established Lyapunov function. Finally, the obtained results are demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

In this paper, we consider the distributed state estimation problem of continuous-time linear time-invariant (LTI) systems, where communication channels are attacked by stochastic impulsive sequences. In a networked system, the communication channel between an agent and its neighbor is vulnerable to being attacked. Continuous attacks have been widely studied so far, but with the development of attack techniques, intermittent attacks have been emerging, which are more difficult to be identified and detected, and have not been well portrayed and studied. Therefore, this paper investigates a random intermittent injection attack, which leads to abrupt and random changes of the state information transmitted by the neighbors. First, this attack is modeled as a stochastic impulsive sequential attack, where both its impulsive time and impulsive intensity are random. Then a distributed observer under stochastic impulsive sequential attack is proposed. Since the impulsive attack destroys the stability of the system, in order to attenuate the impact of the impulsive attack, a large feedback gain is necessary. By using the graph theory, matrix theory and stochastic analysis, sufficient conditions for the existence of the distributed observer in the sense of mean square and in the sense of almost sure are presented, respectively. Finally, the effectiveness of the proposed distributed observer is verified by numerical simulations. [ABSTRACT FROM AUTHOR]

The containment control problem using only sampled position data for second-order multi-agent systems (MAS) is studied in this paper. We first consider the delay-free case of the containment control protocol and obtain a necessary and sufficient condition regarding the network structure and the system parameters. Then, we obtain a similar necessary and sufficient condition for the case with time delay of the containment control protocol. Finally, several numerical simulations are performed to verify the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

A distributed cooperative control paradigm is proposed to handle the load sharing and transmission power loss optimisation‐based optimal power flow (OPF) problems in DC microgrids, which is based on a distributed finite‐time average consensus algorithm and a linear variable weighted summation algorithm. Firstly, an OPF problem is formulated to minimise the global transmission power loss, which is then solved by a novel distributed OPF regulator in secondary control. Furthermore, a distributed OPF considering load sharing controller is proposed in secondary control, which aims to guarantee that the load sharing deviation is limited to the assigned permissible range and the global transmission power loss is reduced to a minimum simultaneously. Compared to existing methods, these two control algorithms are developed in a completely distributed fashion, and the load distribution matrix and conductance matrix of DC microgrids are not needed. The effectiveness of the proposed control methods is verified by simulation results. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem of hybrid multi-agent systems, where the multiple discrete-time and continuous-time dynamic individuals constitute a hybrid multi-agent group. Firstly, a hybrid event-triggered method is proposed. Under this method, the hybrid consensus can be achieved asymptotically. Besides, the Zeno-behavior of the hybrid multi-agent system will not make an appearance due to the special design of the hybrid event-triggered conditions. Then, a self-triggered algorithm is further proposed to avoid the continuous monitoring of event-triggered conditions. Finally, several simulation examples are presented which are comparative and show the effectiveness of the two method. Moreover, the impact of the parameters in the main results is analyzed. [ABSTRACT FROM AUTHOR]

In this study, the controllability of multi‐agent systems with second‐order dynamic under discrete‐time model, which evolve on two time scales. The authors first characterise the systems by difference equations with a singular perturbation parameter. Then, in order to get rid of the singular perturbation parameter, they split the systems into a slow subsystem and fast subsystem based on the iterative method and approximate approach. Moreover, according to matrix theory, they deduce a lot of necessary and/or sufficient controllability criteria of the systems. In particular, a second‐order controllability criterion only depending on the eigenvalues of matrices is proposed, which is more easy‐to‐use and efficient. A simulation example is lastly given to clarify the validity of all theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the consensus problem of discrete-time multiagent systems (DTMASs), which are subject to input saturation and lack of the information of agent dynamics. In the previous works, the DTMASs with input saturation can achieve semiglobal consensus by utilizing the low gain feedback (LGF) method, but computing the LGF matrices by solving the modified algebraic Riccati equation requires the knowledge of agent dynamics. In this paper, motivated by the reinforcement learning method, we propose a model-free Q-learning algorithm to obtain the LGF matrices for the DTMASs achieving global consensus. Firstly, we define a Q-learning function and deduce a Q-learning Bellman equation, whose solution can work out the LGF matrix. Then, we develop an iterative Q-learning algorithm to obtain the LGF matrix without the requirement of the knowledge about agent dynamics. Moreover, the DTMASs can achieve global consensus. Lastly, some simulation results are proposed to validate the effectiveness of the Q-learning algorithm and show the effect on the rate of convergence from the initial states of agents and the input saturation limit. [ABSTRACT FROM AUTHOR]

Distributed observer is an effective scheme for state estimation of a targeted system, utilizing a network of sensors to perform local output measurements. In this article, the problem of designing a distributed observer for a linear time‐invariant system with external disturbances is addressed. The objective is to perform state estimation of such a system while simultaneously mitigating the impact of external disturbances and maintaining the distributed communication characteristics among the sensors. To achieve this, a completely distributed observer with robustness against disturbances is developed by combining the high‐gain observer technique and the adaptive coupling strength strategy. Initially, a traditional high‐gain observer is used for the state estimation on the observable subsystem, and subsequently a high‐gain observer without peaking is introduced to avoid the peaking phenomenon. Finally, numerical simulations are presented to verify the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem for directed positive multiagent systems with nonlinear control input. The directed topology is supposed to be strongly connected. For the case of sector input nonlinearities, the non-negative global consensus conditions are presented by using a novel analysis method which directly considers the nonlinear input, and the feedback matrices are obtained with convex optimization method by solving the quadratic matrix inequalities subject to non-negative constraints. For the case of saturation-type sector input nonlinearities, the global consensus and local consensus results are analyzed, respectively. With the properties of Metzler matrix, the non-negative consensus results are further extended to the strongly connected and balanced positive multiagent systems subject to (saturation-type) sector input nonlinearities and parameter uncertainties. The results are simplified, and the feedback matrices can be given by solving iterative linear matrix inequality with non-negative constraints. Two simulation examples and a practical electrical circuit model are finally carried out to verify the proposed control schemes. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the time-varying formation problem of a linear multi-agent system (MAS) based on sampled data with multiple leaders. The leader group and the follower group form the MAS. Followers are driven to reach the time-varying formation where the center of the formation is the convex combination of the states of the leaders. First, a time-varying formation control protocol with sampled data is proposed, while communication among followers is only occurred at sampling instants, which reduces the waste of communication energy significantly. Second, sufficient conditions for the MAS achieving the desired time-varying formation under sampling with multiple leaders are derived. In the theoretical analysis, a Lyapunov function is constructed to derive sufficient conditions based on formation protocol with sampled data for the MAS reaching time-varying formation. In addition, under formation control with sampled data, the problems of time-varying formation of MAS with one leader and time-invariant formation of MAS with multiple leaders are the special cases of the problem discussed in this paper. Finally, one example is presented to demonstrate the obtained theoretical analysis. [ABSTRACT FROM AUTHOR]

Abstract This paper studies the observer-based edge-consensus of linear discrete-time multi-agent systems on undirected networks, in which the state of each edge is subject to nonnegative constraint, and the input of each edge is limited by actuator saturation. By utilizing the MARE-based low-gain output feedback method and the positive system theory, the observer-based edge interacting algorithm is developed to guarantee the nonnegative edge-consensus. Meanwhile, the sufficient conditions are found to guarantee the nonnegative edge-states and the bounded control input. In addition, the edge-consensus protocol and the sufficient conditions do not use the global information of communication network, which are only dependent on the edge number and the vertex number of communication network. Finally, a case is developed to verify the effectiveness and feasibility of the theoretical result. [ABSTRACT FROM AUTHOR]

, The authors study the semi‐global edge‐consensus of linear discrete‐time multi‐agent systems subject to edge state positive constraint and input saturation. By virtue of the positive system theory and low‐gain feedback method, the distributed control protocols for undirected and directed networks are designed to guarantee the non‐negative edge‐consensus with input saturation. Then, sufficient conditions, which can guarantee the edge‐consensus together with keeping the positive edge state constraint and avoiding the input saturation, are provided. Finally, two examples are presented to verify the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the controllability problems for heterogeneous multiagent systems (MASs) with two-time-scale feature under fixed topology. Firstly, the heterogeneous two-time-scale MASs are modeled by singular perturbation system with a singular perturbation parameter, which distinguishes fast and slow subsystems evolving on two different time scales. Due to the ill-posedness problems caused by the singular perturbation parameter, we analyze the two-time-scale MASs via the singular perturbation method, instead of the general methods. Then, we split the heterogeneous two-time-scale MASs into slow and fast subsystems to eliminate the singular perturbation parameter. Subsequently, according to the matrix theory and the graph theory, we propose some necessary/sufficient criteria for the controllability of the heterogeneous two-time-scale MASs. Lastly, we give some simulation and numerical examples to demonstrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a self-triggered algorithm for leader-following consensus of general linear multi-agent systems with input time delay is proposed. It is shown that the leader-following consensus can be reached asymptotically and the Zeno-behaviour of triggering time sequences can be excluded. Under this algorithm, the next exact triggering time instant of each agent can be computed by the local information at the previous triggering time instant. Continuous communication, monitoring of measurement error and updating of controller input are thus avoided. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the controllability for an interconnected two-time-scale second-order multi-agent system. Firstly, to eliminate the singular perturbation parameter, we separate the multi-agent system into slow subsystem and fast subsystem by using singular perturbation methods. Then, based on matrix theory, some necessary and/or sufficient criteria are derived for second-order controllability of two-time-scale multi-agent systems with multiple leaders. Moreover, we propose some easy-to-use second-order controllability criteria determined only by eigenvalues of system matrices. Lastly, the effectiveness of the proposed theoretical results is illustrated by a simulation example. [ABSTRACT FROM AUTHOR]

This paper focuses on addressing the consensus problem of edges for both undirected and directed nodal networks whose edges are described by nominal or uncertain positive linear systems. The definition of line graph is given, and the similar properties and connections between the two types of graphs are established. Based on the rigorous theoretical analysis, distributed positive consensus algorithms are proposed, and the main results are given without utilizing the global interaction information. Subsequently, sufficient conditions for consensus with positivity constraint are given via the vertex number and the edge number of the original nodal network. Furthermore, according to the properties of Metzler matrix, we also solve the consensus problem for multiple edges which are modeled by uncertain positive systems. Some simulation studies are finally presented to verify the feasibility and effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the event‐triggered leader‐following consensus problem of general linear fractional‐order multiagent systems subject to input delay on directed graph is investigated. A distributed event‐triggered control protocol with input delay is proposed firstly. By applying the properties of the Mittag‐Leffler function, the technique of inequality, and the matrix theory, some consensus criteria for the fractional‐order multiagent systems are obtained. It is shown that the dynamic leader can be tracked by the followers for any bounded delay, and the followers receive and update their control protocol at some discrete time instants. Some simulation results are presented to illustrate the effectiveness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Abstract Since many practical physical phenomena can be depicted more accurately and suitablely by fractional-order models, this work addresses the event-triggered consensus tracking for the fractional-order multi-agent systems (FOMASs) governed by general linear models. Firstly, a distributed event-triggered control algorithm relied on state feedback is derived. Then, according to the Laplace transform, the Mittag-Leffler function, the comparison test of improper integral, and the technique of inequality, some consensus criteria are obtained to ensure all followers can track a dynamic leader and Zeno behavior can be avoided. Lastly, some numerical simulation results are provided to verify the effectiveness of the event-triggered method. [ABSTRACT FROM AUTHOR]

The robust tracking control problem of the leader‐follower multiagent systems affected by asymmetric input saturation and external disturbances is addressed in this article, by following three steps. First, an radial basis function neural network (RBFNN) is developed to estimate the external disturbances and supersaturation, where the supersaturation is induced by asymmetric saturation actuator. Second, combining with the developed radial basis function neural network, a reduced‐order observer‐based static protocol and a reduced‐order observer‐based adaptive one are designed for leader‐follower systems with un‐directed communication topology as well as those with directed communication topology, respectively. Third, some mild premises are given to guarantee the semiglobal robust leader‐follower consensus for the above mentioned two kinds of multiagent systems. Finally, the theoretical results are verified by several numerical simulations. [ABSTRACT FROM AUTHOR]

The complexity of relationships between bridge inspection presents a significant challenge for the answer system. Sparse knowledge graph (KG) due to limited triples further compounds the issue. To overcome this, this paper proposes a dynamic reasoning strategy for bridge inspection question answering. The framework comprises a teacher-student network and dynamic reasoning strategy. The teacher network, based on the neural state machine (NSM), acquires auxiliary intermediate supervision signals. Its output provides probability distribution and entity embedding as input for the student network. The student network, also NSM-based, provides accurate answers with the aid of intermediate supervision signals. To handle incomplete KG, the dynamic reasoning strategy incorporates knowledge embedding, updating the KG by capturing contextual information of each related entity node in relation to the question. Experiments on the bridge inspection dataset demonstrated the effectiveness of this method, outperforming other approaches. [ABSTRACT FROM AUTHOR]

This study addresses the group controllability of continuous‐time multi‐agent systems. The problem is investigated in the leaderless framework where the whole group is consisted of a number of dynamic agents with autonomous capability, which can complete the large‐scale complex task through local interaction and can be divided into some subgroups. This study concentrates on the group controllability problems of continuous‐time multi‐agent systems, gives the general definition of the group controllability, and establishes group controllability criteria. Sufficient and necessary conditions are derived for the group controllability of continuous‐time multi‐agent systems. Finally, the numerical example and simulations are given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Summary: The robust semiglobal swarm tracking problem of N coupled harmonic oscillators and 1 actual leader with input saturation and external disturbance on a directed communication topology is considered, in which the N coupled harmonic oscillators are referred to followers. First, the low‐and‐high gain feedback technique is introduced to construct a relative state‐dependent control algorithm. Then, an observer‐based control algorithm is designed based on the low‐and‐high gain feedback technique and the high‐gain observer design methodology. Sufficient conditions are derived to guarantee robust semiglobal swarm tracking for state‐feedback control and output‐feedback control, respectively. Numerical simulations are finally provided to verify the theoretic results. [ABSTRACT FROM AUTHOR]

The problem of leader-following attitude consensus for multiple rigid-body systems is addressed for communication limitation in this paper. The leader and followers are described in unit quaternions forms. For each follower, a nonlinear finite-time distributed observer is proposed to estimate the states of the leader, and the event-triggered finite-time sliding mode controllers are constructed by using the estimation information to decrease the system's communication and computation consumption. The result demonstrates that in a finite time, the attitude tracking error can converge to an invariant set, and the communication interaction is decreased by the proposed event-triggered-based controller. Moreover, Zeno behavior is rigorously proved to be excluded, and the lower bound of the triggered time interval is provided. Finally, a numerical simulation is provided to validate the efficiency of the proposed control protocol. [ABSTRACT FROM AUTHOR]