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This paper proposes a novel importance-based persistent coverage for environments with hotspots. Multiple quadrotors are utilized to maintain coverage while acquiring high-quality information over prioritized regions by lowering the altitude. To achieve this, the approach utilizes distributed communication protocols and cost functions to address the tradeoff between wider coverage and better quality information. The cost functions determine three-dimensional waypoints based on coverage levels, sensor resolution, and Euclidean distance. Voronoi tessellations are used locally for efficient computation and collision avoidance. Trajectories of the quadrotors are generated based on quadrotor dynamics using error functions that take into account state information and desired waypoints. The proposed approach is validated through simulations, comparisons, and experiments for multi-agent systems under quadrotor dynamics. Further, metrics of performance analysis are formulated that show consistent coverage levels and differences to assess the novel importance-based approach. The simulations and experiments demonstrate the feasibility and effectiveness of the approach, with prioritized regions receiving higher sensor resolution while maintaining persistent coverage of the environment. • Novel importance-based persistent coverage for information acquisition over hotspots. • Quadrotor waypoints based on information resolution and decaying environmental costs. • Distributed communication protocols for scalability and low computational complexity. • Real-time importance-based persistent coverage for multi-quadrotor dynamical systems. • Proposed coverage with varying velocities is verified by simulation and experiments. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time consensus of second-order multi-agent systems subject to matched and mismatched disturbances. The derivatives of disturbances are assumed to be bounded. A novel integral sliding mode-based observer is presented by utilizing the super-twisting algorithm to estimate the agent states. The estimations can achieve the convergence to the leader in a fixed time. Furthermore, the corresponding fixed-time controller is developed to make the agents converge to the estimated states. As the estimated states converge to the leader, the agents will track the leader states with the help of estimated states. In addition, the overall convergence of multi-agent systems is non-monotonic due to the disturbances. It is theoretically shown that the proposed control approach can maintain a bounded convergence and get the consensus of multi-agent systems in a fixed time. Some simulations are presented to verify the effectiveness of the proposed control protocol. [ABSTRACT FROM AUTHOR]

The event-triggered time-varying formation tracking for a class of second-order multi-agent systems (MASs) subject to a non-cooperative leader is investigated in this paper. First, in the presence of the unknown input of the leader and external disturbances, a distributed observer with adaptive parameters is put forward for followers to estimate the velocity tracking error. Then, based on the estimated tracking error and an auxiliary variable, a finite time formation controller is further constructed, which is updated depending on a pre-designed event-triggered mechanism. As a result, the desired time-varying formation configuration can be realized in finite time with less communication resource consumption. It's noted that the constructed formation strategy doesn't rely on any global information and thus is fully distributed. The stability of the controlled multi-agent system is proved rigorously and it's verified that event-triggered intervals are with a positive lower bound. At last, simulations are carried out to illustrate the effectiveness of the presented algorithm. [ABSTRACT FROM AUTHOR]

This paper solves the finite-time consensus problem for discrete time multi-agent systems (MASs) where agents update their values via linear iteration and the interactions between them are described by signed digraphs. A sufficient condition is presented that the agents can reach consensus on any given linear function of multiple initial signals in finite time, i.e., there exists an eventually positive Laplacian-based matrix associated with the underlying graph. We prove that the linear iterative framework "ratio consensus" developed for unsigned graphs in the literature can be extended to the computation for signed graphs with appropriate modifications. Our method weakens the limitation of the iterative framework on the "marginal Schur stability" of the weight matrix without increasing the computational complexity. Reaching average consensus on unsigned graphs as in the literature is regarded as a special case of our algorithm. Two illustrative examples are presented to demonstrate the correctness of the proposed results. [ABSTRACT FROM AUTHOR]

In this paper, a resilient distributed consensus algorithm is proposed based on multi-agent system to defend against the Byzantine attack. Two attack scenarios including node attack and edge attack are considered and the differences between them are described, in which the edge attack scenario is seldom considered before. The assumption for a network under g -local attacks is relaxed from (2 g + 1) -robust directed graph to (g + 1) -robust one based on a novel filtering method. The convergence and optimality are guaranteed by theoretical analysis, which ensures all the agents without attack can make an agreement and converge to a certain range. The simulation results show that for the two attack scenarios, the proposed algorithm can converge to the optimal solution of the compensation problem and the original problem, respectively. The proposed algorithm is more effective and has faster convergence speed compared with the contrast one. [ABSTRACT FROM AUTHOR]

Distributed coordination of multi-agent systems (MASs) has been investigated for many years, and fractional-order calculus has been proved that it can model the dynamics more accurately in certain circumstances. Hence, in this paper, combining the above two aspects, the distributed coordination of fractional-order MASs (FOMASs) is researched, which is a promising topic. Besides, in this paper, the uncertainty, inherent nonlinearity and external disturbances are taken into consideration, aiming at achieving the robust consensus tracking. In particular, the uncertain parameters will be identified from an optimization perspective using artificial bee colony algorithm (ABC). Firstly, to ameliorate the performance of the standard ABC, a hybrid ABC (hABC) incorporating two groups of searching mechanisms is designed, it facilitates the identification of unknown parameters. After obtaining the identified parameters, an efficient distributed nonlinear controller is raised to fulfill the robust consensus tracking. Finally, experiments prove that the designed parameters identification approach can successfully estimate the uncertain parameters with high accuracy, besides the designed control algorithm can robustly control the FOMASs. [ABSTRACT FROM AUTHOR]

In this paper, we address the distributed convex optimization problems for multi-agent systems. In our research, it is assumed that each agent in the multi-agent system could merely interact with its neighbors via a directed graph and is available to its own cost function. We then utilize the push-sum distributed dual averaging (PS-DDA) algorithm to tackle with the distributed optimization problem. However, we consider that there exist subgradient delays in PS-DDA algorithm. The proof of the main result which shows that the PS-DDA algorithm with subgradient delays converges and the error possesses sublinear growth of a rate O (τ 2 T − 0.5) , where T denotes the total amount of iterations, is detailed presented in this paper. Finally, a numerical example is simulated to show the performance of the algorithm we study in this paper. [ABSTRACT FROM AUTHOR]

This paper considers a nonsmooth constrained distributed convex optimization over multi-agent systems. Each agent in the multi-agent system only has access to the information of its objective function and constraint, and cooperatively minimizes the global objective function, which is composed of the sum of local objective functions. A novel continuous-time algorithm is proposed to solve the distributed optimization problem and effectively characterize the appropriate gain of the penalty function. It should be noted that the proposed algorithm is based on an adaptive strategy to avoid introducing the primal-dual variables and estimating the related exact penalty parameters. Additional, it is demonstrated that the state solution of the proposed algorithm achieves consensus and converges to an optimal solution of the optimization problem. Finally, numerical simulations are given and the proposed algorithm is applied to solve the optimal placement problem and energy consumption problem. [ABSTRACT FROM AUTHOR]

The problem of simultaneous fault detection and containment control of linear continuous-time multi-agent systems with multi-leaders is firstly addressed in this paper. Distributed detection filters are designed using relative output information and local input information among agents to detect the actuator faults and sensor faults in agents, and H ∞ / H − formulation for this problem is presented in the finite frequency domain. In order to solve the complexity problems caused by multiple leaders in the system, the influence of leaders on the residual signals of followers is taken into account in the design of the proposed detection filter, and through the reasonable design of the controller, the containment control of the followers can also be achieved simultaneously. The controller and filter parameters are obtained by solving the optimization problem with linear matrix inequalities(LMI) constraints. Furthermore, faults are allowed to occur in leaders in this paper, and an effective algorithm is proposed to detect and isolate faults in the system. At last, an adjustable filter structure is proposed to prevent the followers from being influenced by the failure leader, which is of great practical significance. Finally, to illustrate the effectiveness of the proposed methodology, a simulation study is provided. [ABSTRACT FROM AUTHOR]

This paper considers the containment control problem for the discrete-time nonlinear multi-agent systems with unknown parameters and completely unknown control gains. In this paper, the dynamics of each agent are nonlinearly coupled with the neighbors' states. To deal with the unknown parameters and control gains, a projection-type estimation algorithm is designed with the singular value avoided in the estimated control gains. The bounded estimation errors of parameters and control gains are guaranteed by the convergence analysis based on the Lyapunov approach. Then, using the estimated parameters and control gains, a distributed adaptive control protocol with only local information is designed for multi-agent systems. Under the proposed control protocol, the containment of multi-agent systems is guaranteed from a novel viewpoint of the absorbing Markov chain. Furthermore, simulations are carried out to illustrate the effectiveness of the proposed containment control protocol. [ABSTRACT FROM AUTHOR]

In this paper, the distributed constrained optimization problem over a directed graph is considered. We assume that the digraph has a row-stochastic adjacency matrix, which corresponds to the case when agents assign weights to the received information individually. We present an algorithm that converges to the optimal solution even with a time-varying stepsize which is not attenuated to zero. The choice of stepsizes is relatively easy. The usable type of stepsizes is added. The diminishing or constant stepsizes can be used in our algorithm. Equality constraints and set constraints are also considered in this paper. Convergence analysis of the proposed algorithm relies on a conversion theorem between column-stochastic and row-stochastic matrices. Finally, the results of the numerical simulation are provided to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper focuses on designing a leader-following event-triggered control scheme for a category of multi-agent systems with nonlinear dynamics and signed graph topology. First, an event-triggered controller is proposed for each agent to achieve fixed-time bipartite consensus. Then, it is shown that the Zeno-behavior is rejected in the proposed algorithm. To avoid intensive chattering due to the discontinuous controller, the control protocol is improved by estimating the sign function. Moreover, a triggering function is proposed which avoids continuous communication in the event-based strategy. Finally, numerical simulations are given to show the accuracy of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the affine formation control problem for multi-agent systems with prescribed convergence time is investigated. Firstly, on the basis of a time-varying scaling function, a distributed continuous control algorithm is designed, under which a stationary affine formation of the nominal configuration is able to be achieved within a prescribed time. Secondly, to track a time-varying formation within the prescribed time, a distributed control protocol is proposed by employing a leader–follower control strategy. Furthermore, the boundary layer technique is adopted to avoid chattering effect. Finally, simulation examples are provided to demonstrated the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

This paper researches the output consensus problem of heterogeneous linear multi-agent systems with cooperative and antagonistic interactions. Two fixed-time state compensator control approaches, one static dynamic and the other distributed adaptive dynamic, are considered for heterogeneous systems subject to logarithmic quantization. Then, a fixed-time output regulation control protocol is constructed to cope with the problem of bipartite output consensus and adaptive fixed-time output consensus of heterogeneous systems which is fully distributed without any global information. Besides, the fully distributed adaptive algorithm is employed to calculate the system matrix of leader and it's also effectively eliminated the harmful chattering. Finally, two simulations are carried out to testify the feasibility of theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of identifying the interaction geometry of a set of agents, whose collective goal are to achieve consensus under an agreement protocol. By classifying agents into different subsets based on their behavior, as well as introducing the so-called input and output agents, a relationship between the transfer function matrix and the identifiability of system parameters is established. Specifically, two cases are considered. If the set of input agents coincides with the set of output agents, the number of edges in the input agent set, in the complement of input agent set, and between these two sets can be uniquely identified. Thus, the search space of feasible graphs becomes much smaller. The problem can be solved in polynomial time, and an algorithm is provided. Moreover, if all the agents in the system are output agents, parameters of the system can be uniquely identified, and an algebraic method is given to exactly recover the graph topology. A numerical example illustrates the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

For multi-agent system (MAS), most of existing iterative learning control (ILC) algorithms consider about the tracking of reference defined over the whole trial interval, while the point-to-point (P2P) task, where the emphasis is placed on the tracking of intermediate time points, has not been explored. Thus, a distributed ILC method is proposed, in which each agent updates the feedforward control input by learning from the experience of itself and its neighbors in previous repeated tasks to achieve the goal of improving performance. In addition, for the sake of reducing the burden of data transmission in MAS, effective data quantization is essential. In this case, the quantitative measurement of the error of the tracking time points is further used in the ILC updating law. In order to accommodate this requirement, a distributed point-to-point iterative learning control (P2PILC) with tracking error quantization for MAS is first proposed in this paper. A necessary and sufficient condition is presented for the asymptotical stability of the proposed algorithm, and simulation results show the effectiveness of it finally. [ABSTRACT FROM AUTHOR]

In this paper, we consider the distributed optimization problems with linear coupling constraint of general homogeneous and heterogeneous linear multi-agent systems under weighted-balanced and strongly connected digraphs. In order to control all agents converge to the optimal output, we propose distributed control laws, therein, the optimal output can make the global cost function reach minimum. Then we guarantee the convergence of the proposed algorithms by the properties of Laplacian matrix and Lyapunov stability theorem. Furthermore, we extend the result of heterogeneous linear multi-agent system to the case that dynamics of agents are subject to external disturbances, and prove that the algorithm designed by internal model principle can make all agents reach the optimal output exactly. Finally, we provide examples to illustrate the effectiveness of the proposed distributed algorithms. [ABSTRACT FROM AUTHOR]

This paper solves the leaderless consensus problem of a class of strict-feedback uncertain nonlinear multi-agent systems with unknown control directions and unknown system parameters. Without using the Nussbaum function approach, a novel control scheme is proposed by means of the switching mechanism. The control algorithm guarantees that consensus errors converge to the origin asymptotically, and the amplitude of the control signals are much smaller compared with those using Nussbaum functions. The simulation results illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time consensus problem of leader-follower higher-order multi-agent systems with uncertain nonlinearities is studied, where the uncertainties are assumed to satisfy Hölder conditions. To solve this problem, distributed adding a power integrator method, feedback domination technique and integral sliding-mode control are combined together. Firstly, by using distributed adding a power integrator method, a distributed recursive control scheme is proposed. In the recursive control design, based on feedback domination method, the Hölder conditions of the unknown nonlinearities are introduced into the virtual controllers design. Secondly, on the basis of the designed recursive controllers, integral sliding-mode surfaces are designed and then the corresponding distributed sliding-mode controllers are proposed. The designed sliding-mode controllers guarantee that the finite-time leader-follower consensus problem is solved without using a distributed observer. The stability analysis of the closed-loop systems is presented based on finite-time stability theory. Moreover, simulations show the effectiveness of the proposed consensus algorithms. [ABSTRACT FROM AUTHOR]

Networked predictive control is an effective method to handle time delays and data dropouts in networked control systems, but it is difficult to apply the control strategy to networked multi-agent systems. First, the computational burden will increase exceedingly when the control strategy is applied to networked multi-agent systems. Second, restrictions have to be imposed on the communication topology to implement the control strategy; Third, most existing networked predictive controllers lack robustness to model uncertainties. In this paper, these problems are solved by introducing predicting error to the control scheme. The proposed control strategy not only guarantees consensus and stability of the overall system, but also reduces the computational burden exceedingly. In addition, the proposed algorithm is robust to model uncertainties. At last, the proposed control strategy can be executed in distributed processors, therefore, flexibility and robustness are preserved for the networked multi-agent systems. These features make the control strategy applicable in practice. Digital simulations and experiments based on spacecraft simulators are carried out to verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Time-varying group formation tracking control problems for second-order multi-agent systems with communication delays and multiple leaders are addressed in this paper. The followers are divided into multiple subgroups, and each subgroup is driven to complete the time-varying sub-formation and to track the average state of entire leaders simultaneously. A distributed protocol that considers communication delays and uses only local interaction information is presented. According to Lyapunov-like stability approach, sufficient conditions for the multi-agent systems to realize time-varying group formation tracking with multiple leaders are given. A variable-substitution based method is developed to get the unknown feedback matrix of the protocol and an algorithm is given to summarize the steps to construct the protocol. The theoretical results can be used in the problem of multiple targets enclosed by several subgroups of unmanned aerial vehicles. Finally, numerical examples are applied to verify the feasibility of the proposed results. [ABSTRACT FROM AUTHOR]

Consensus problem in a leader-following multi-agent system with actuator fault is investigated in this paper. By introducing the control allocation and optimal method, a novel distributed controller is proposed to deal with the partial loss of effectiveness and outage fault without reconfiguring the controller. Compared with the existing literatures, the proposed algorithm can guarantee the consensus errors converge to zero asymptotically without the traditional rank assumption. Finally, three simulations are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the problem of distributed output consensus is investigated for heterogeneous multi-agent systems subject to a class of uncertainties in communication channels. The studied uncertainties, leading to a time-varying communication topology modeled as a Markovian switching communication topology and delayed transit information, may happen discontinuously and affect the consensus behavior of multi-agent systems. To mitigate the effects of such uncertainties on output consensus, a novel switching distributed control protocol is proposed, aiming to guarantee output consensus of the studied networks in the mean square sense. Moreover, an algorithm is given to select the required controller gains based on the solutions to a Lyapunov inequality and a group of regulator equations. Along this framework, a simulation example on the IEEE 24 Bus System is presented to demonstrate the effectiveness of the algorithm and the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time time-varying output formation-tracking (FT-TV-OFT) problem of heterogeneous linear multi-agent systems (HL-MASs) is investigated. First, we propose an adaptive finite-time observer for each follower, aiming to estimate not only the leader's state but also the leader's system matrix. Compared with conventional observers, the dependence of the observer parameters on any global information is completely removed. Moreover, exact estimate can be achieved in a finite time. Then, an adaptive algorithm is used to calculate the regulation equations, such that control gains can be obtained. Next, an adaptive distributed controller is constructed to solve the FT-TV-OFT problem. Moreover, we also extend above results to the case of the directed communication topology. Finally, examples are given to demonstrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

In this paper, a control scheme is proposed for a group of elliptical agents to achieve a predefined formation. The agents are assumed to have the same dynamics, and communication among the agents are limited. The desired formation is realized based on the reference formation and the mapping decision. In the control design, searching algorithms for both cases of minimum distance and tangents are established for each agent and its neighbors. In order to avoid collision, an optimal path planning algorithm based on collision angles, and a self-center-based rotation algorithm are also proposed. Moreover, randomized method is used to provide the optimal mapping decision for the underlying system. Two examples and analyses are presented to demonstrate the effectiveness and potential of the new control scheme. [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]

Abstract This paper investigates group consensus for leaderless multi-agent systems with non-identical dynamics. The consensus protocol is put forward in the form of the distributed event-triggered control subject to saturation, which depends on information from neighboring agents at event-triggered instants. In order to exclude the Zeno behavior and save resources, the given event-triggered condition is detected only at discrete sampling times, where the sampling intervals can be variable. Based on the graph theory, Lyapunov–Krasovskii functional method and by adopting the free-weighting matrix technique, some sufficient group consensus criteria in terms of linear matrix inequalities are derived. Furthermore, optimization problems aiming at maximizing the event-triggered parameter and the consensus region are proposed. Finally, numerical simulations illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the rendezvous strategy for a group of unicycle systems with connectivity preservation and collision avoidance. Based on the method of potential functions, a novel distributed control algorithm is proposed for all unicycles. By tuning the design parameters, the unicycles finally aggregate so that the average of the distances is bounded by a pre-specified positive number. It is proved that the connectivity of a minimum spanning tree in the initial topology is guaranteed. The result is then extended to multiple unicycles with heterogenous input disturbances. Potential function is further modified to handle the disturbances. Illustrative example is presented to show the improvements and effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper considers the problem of the leader-following consensus of generally nonlinear discrete-time multi-agent systems with limited communication channel capacity over directed fixed communication networks. The leader agent and all follower agents are with multi-dimensional nonlinear dynamics. We propose a novel kind of consensus algorithm for each follower agent based on dynamic encoding and decoding algorithms and conduct a rigorous analysis for consensus convergence. It is proved that under the consensus algorithm designed, the leader-following consensus is achievable and the quantizers equipped for the multi-agent systems can never be saturated. Furthermore, we give the explicit forms of the data transmission rate for the connected communication channel. By properly designing the system parameters according to restriction conditions, we can ensure the consensus and communication efficiency with merely one bit information exchanging between each pair of adjacent agents per step. Finally, simulation example is presented to verify the validity of results obtained. [ABSTRACT FROM AUTHOR]

This paper investigates the consensus problem for event-triggered multi-agent systems (MAS) subject to external disturbances, time delays and packet losses as well as Sigma–Delta ( Σ Δ ) quantizer who has a finite number of quantization level simultaneously. Firstly, we transform this problem into a robust H ∞ control by defining an appropriate controlled output. Secondly, we give a criteria to judge the consensusability of asynchronous event-triggered MAS and present a sufficient condition in terms of matrix inequalities to get the state feedback controller׳s parameters. Moreover, the maximal allowable number of successive packet losses is also given, and the algorithm designed here has made considerable contributions to save communication resources. Finally, numerical examples are given to show the effectiveness of the proposed consensus protocol. [ABSTRACT FROM AUTHOR]

In this paper a leader-following discrete type multi-agent consensus control problem with both switching and fixed interaction topologies has been discussed. Multi-agent system subjected to external disturbances is considered and dynamic output feedback based consensus controller was designed to ensure that the H ∞ performance was achieved. A Powerful LMI algorithm is used to analyze consensus of multi-agent system. Besides, the feedback gain matrix is obtained through two LMIs that guarantee the existence of common matrices satisfying consensus of multi-agent systems under dynamically interaction topology. Finally, a simulation example is presented to demonstrate the robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This paper is concerned with a consensus problem of a class of second-order multi-agent systems with nonuniform time-delays. A distributed consensus algorithm is adopted to drive all agents to reach consensus and move together with a constant velocity. By a frequency domain approach, an upper bound on the maximum of the time-delays that can be tolerated is given for the consensus of the system. [Copyright &y& Elsevier]

Abstract: This paper studies the consensus problem of the multi-agent systems with parallel Luenberger observers. First, the structure of the cooperative system is established, where the output of the built-in Luenberger observer for each agent is used as its local control input and the cooperative control input combining with the cooperative measurement output is utilized as the input of the observers. Based on the structure of the closed-loop system, the consensus problem is then analyzed. In addition, two methods for designing the controller gains are provided. By virtue of the proposed structure, it is pointed out that the design of the controller gains and the observer parameters can be carried out separately. Finally, by resorting to the gradient flow method, an optimization algorithm is proposed to reduce the influence of the environmental noises. The effectiveness of the obtained results is shown through a numerical example. [Copyright &y& Elsevier]