Distributed Fixed‐Time Coordinated Tracking for Nonlinear Multi‐Agent Systems Under Directed Graphs

This paper is concerned with the fixed‐time coordinated tracking problem for a class of nonlinear multi‐agent systems under detail‐balanced directed communication graphs. Different from conventional finite‐time coordinated tracking strategies, the fixed‐time approach developed in this paper guarantees that a settling time bound is prescribed without dependence on initial states of agents. First, for the case of a single leader, a distributed protocol based on fixed‐time stability techniques is proposed for each follower to accomplish the consensus tracking in a fixed time. Second, in the presence of multiple leaders, a new distributed protocol is proposed such that states of followers converge to the dynamic convex hull spanned by those of leaders in a fixed time. In addition, for a class of linear multi‐agent systems, sufficient conditions that guarantee the fixed‐time coordinated tracking are provided. Finally, numerical simulations are given to demonstrate the effectiveness of the theoretical results.     

Fixed‐Time Consensus of Multi‐Agent Systems with Directed and Intermittent Communications

This paper proposes a new class of nonlinear protocols for fixed‐time consensus in networked agents with directed and intermittent communications. First of all, based on the assumption of a common positive dwell time for all successful links, it is theoretically shown that the asymptotical consensus can be achieved if the interaction topology with some fixed length of time has a spanning tree. Then, if the length sum of time intervals, over which the directed interaction topology contains a spanning tree, is larger that a threshold value, which is independent of initial conditions, the system will solve a fixed‐time consensus problem. Furthermore, in light of the mirror operation principle of graph theory, the proposed protocol is extended to solve the fixed‐time consensus problem if a common positive dwell time for all active links is strongly connected without the detailed balanced condition. Finally, the effectiveness of the theoretical results is illustrated by simulation results.     

Adaptive Leader‐Following Consensus for Uncertain Nonlinear Multi‐Agent Systems

This paper is concerned with the adaptive leader‐following consensus for first‐ and second‐order uncertain nonlinear multi‐agent systems (NMASs) with single‐ and double‐integrator leader, respectively. Remarkably, the control coefficients of the followers need not belong to any known finite interval, which makes the systems in question essentially different from those in the related works. Moreover, parameterized unknowns exist in the nonlinearities of the followers, and unknown control input is imposed on the leader, which make the problems difficult to solve. To compensate for these uncertainties/unknowns, the leader‐following consensus protocols are constructed by employing adaptive technique for the first‐order and the second‐order NMASs. Under the designed adaptive consensus protocols and the connected graph, the leader‐following consensus is achieved. Finally, two examples are given to show the effectiveness of the proposed leader‐following consensus protocols.     

Finite‐Time Consensus Problem for Second‐Order Multi‐Agent Systems Under Switching Topologies

This paper investigates the finite‐time consensus problem for multi‐agent systems with second‐order individual dynamics under switching topologies. A distributed continuous‐time protocol is designed to guarantee finite‐time consensus for homogeneous agents without predetermined leaders, i.e., it ensures agents asymptotically converge to an average consensus within finite time, even if the interaction topology among them is time‐varying but stepwise jointly‐connected. In particular, it introduces a distributed continuous‐time protocol to reach consensus in finite time and reduce the chattering together. Finally, the simulation results are also given to validate the proposed approach.     

Distributed Adaptive Event‐Triggered Control for Leader‐Following Consensus of Multi‐Agent Systems

This paper studies the leader‐following consensus problem for Lipschitz nonlinear multi‐agent systems using novel event‐triggered controllers. A distributed adaptive law is introduced for the event‐based control strategy design such that the proposed controllers are independent of system parameters and only use the relative states of neighboring agents, and hence are fully distributed. Due to the introduction of an event‐triggered control scheme, the controller of the agent is only triggered at it's own event times, and thus reduces the amount of communication between controller and actuator and lowers the frequency of controller updates in practice. Based on a quadratic Lyapunov function, the event condition which uses only neighbor information and local computation at trigger instants is established. Infinite triggers within a finite time are also verified to be impossible. The effectiveness of the theoretical results are illustrated through simulation examples.     

Leader‐Following Consensus of Multi‐Agent System with Diffusion

This paper is concerned with the leader‐following consensus problem for multi‐agent systems consisting of one stationary leader and multiple cooperative followers, where the controlling effect of each follower depends on its own state. It is noted that the influence of diffusion among followers is taken into account and the system is modeled by reaction‐diffusion equations. With the assumption of the followers' initial states, a linear control protocol is designed. Based on algebraic graph theory, the method of energy estimates, and Sobolev embedding theorem, the sufficient conditions guaranteeing the leader‐following consensus under the proposed control protocol are provided. Numerical examples illustrate the effectiveness of the theoretical results.     

Synchronization of Heterogeneous Multi‐Agent Systems by Adaptive Iterative Learning Control

In this work, under a repeatable control environment, an adaptive iterative learning control method is applied to synchronize a group of uncertain heterogeneous agents. The agent dynamics are modeled by nonlinear equations, which contain both parametric and non‐parametric uncertainties. Furthermore, the uncertainties are assumed to be general nonlinear terms instead of the global Lipschitz functions. The communication among the followers is depicted by an undirected and connected graph, meanwhile, the virtual leader's trajectory is only accessible to a small portion of the followers. The proposed learning rules enable all the followers to learn and handle both parametric and non‐parametric uncertainties based on the local information such that the followers can synchronize their trajectories to the desired one. In comparison with the existing literature, most works assume first or second order nonlinear systems, and perfect initial conditions. In order to mitigate the identical initialization condition, the applicability of alignment condition and initial rectifying action are further explored. In addition, our developed algorithms can be applied to general high order nonlinear systems. Finally, synchronization examples of networked robotic manipulators are presented to demonstrate the effectiveness of the developed methods.     

Leader‐Following Output Synchronization for a Class of Uncertain Nonlinear Multi‐Agent Systems Under Uniformly Connected Network

In this paper we study the cooperative global output regulation problem of a class of uncertain nonlinear multi‐agent systems under dynamic network topology. Distributed dynamic observers are introduced to estimate the states of the leader system or the called exosystem. Furthermore, we propose a multi‐channel input version of the changing supply rate theorem, through which the changing supply rate technique can be applied to the subsystem with multiple channels of the control inputs, and therefore control laws can be designed in a fully distributed way. As opposed to the existing results, in the current paper we allow the communication network topology to be uniformly connected. Finally, we apply our result to a group of well‐known Lorenz systems.     

NNs‐Based Event‐Triggered Consensus Control of a Class of Uncertain Nonlinear Multi‐Agent Systems

We are concerned with the consensus problem for a class of uncertain nonlinear multi‐agent systems (MASs) connected through an undirected communication topology via event‐triggered approaches in this paper. Two distributed control strategies, the adaptive centralized event‐triggered control one and adaptive distributed event‐triggered control one, are presented utilizing neural networks (NNs) and event‐driven mechanisms, where the advantages of the proposed control laws lie that they remove the requirement for exact priori knowledge about parameters of individual agents by taking advantage of NNs approximators and they save computing and communication resources since control tasks only execute at certain instants with respect to predefined threshold functions. Also, the trigger coefficient can be regulated adaptively with dependence on state errors to ensure not only the control performance but also the efficiency of the network interactions. It is proven that all signals in the closed‐loop system are bounded and the Zeno behavior is excluded. Finally, simulation examples are presented for illustration of the theoretical claims.     

Distributed Containment Control for Nonlinear Multi‐Agent Systems with Time‐Delayed Protocol

In this paper, the containment control problem is considered for nonlinear multi‐agent systems with directed communication topology. Under the guidance of designed distributed communication protocols with/without previous state information, the followers are expected to converge to a dynamic convex hull spanned by multiple leaders. Two multi‐step algorithms are proposed to construct the corresponding protocols, the state feedback protocol and the delay‐coupled protocol, under which the containment control can be achieved asymptotically. Furthermore, it is found that the delay‐coupled protocol is rather sensitive to time delays. That is, real‐time tracking will become impossible by only using long‐dated previous state information. Finally, a numerical example is given to demonstrate the applicability and efficiency of the proposed schemes.     

Synchronization of General Linear Multi‐Agent Systems With Measurement Noises

This paper studies the synchronization of general linear multi‐agent systems with measurement noises in mean square. It shows that the conventional consensus protocol is efficient and robust to the additive and multiplicative measurement noises in mean square. For the additive measurement noises which are independent of the relative‐states, it shows that the multi‐agent systems can achieve synchronization in practical mean square. For the multiplicative measurement noises which are dependent of the relative‐states, it shows that the multi‐agent systems can achieve synchronization in (strict) mean square. Furthermore, the new consensus protocol is better than the conventional one at some specific situations, i.e., the multi‐agent systems with additive measurement noises can also achieve synchronization in (strict) mean square. Numerical simulations are also provided and the results show highly consistent with the theoretical results.     

Finite‐Time Stabilization of Stochastic High‐Order Nonlinear Systems

This paper considers the problem of global finite‐time stabilization in probability for stochastic high‐order nonlinear systems in which the power order is greater than or equal to one and the drift and diffusion terms satisfy weaker growth conditions. Based on stochastic Lyapunov theorem on finite‐time stability, via the combined adding one power integrator and sign function method, constructing a Lyapunov function and verifying the existence and uniqueness of solution, a continuous state feedback controller is designed to guarantee the closed‐loop system globally finite‐time stable in probability.     

Exponential Consensus for Nonlinear Multi‐Agent Systems with Communication and Input Delays via Hybrid Control

This paper aims to investigate the exponential leader‐following consensus for nonlinear multi‐agent systems with time‐varying communication and input delays by using hybrid control. Based on the Lyapunov functional method, impulsive differential equation theory and matrix analysis, we show that all the followers can achieve leader‐following consensus with the virtual leader exponentially even if only a fraction of followers can obtain the leader's information. Two classes of exponential consensus criteria as well as the convergence rates for the controlled multi‐agent systems are presented under very relaxed interaction topology conditions, i.e., the directed interaction topology among the followers is only required to have p(p>1) disjoint strong components. Finally, two numerical examples are given to validate the proposed theoretical results.     

Consensus Problem with a Reference State for Fractional‐Order Multi‐Agent Systems

In this paper, the consensus problem of fractional‐order multi‐agent systems with a reference state is studied under fixed directed communication graph. At the beginning, the convergence speeds of fractional‐order multi‐agent systems are investigated based on the Mittag‐Leffler function. Then, a common consensus control law and a consensus control law based on error predictor are proposed, and it is shown that the consensus tracking can be achieved using the above control laws when a communication graph has a directed spanning tree. Finally, the convergence speeds of fractional‐order systems are compared, and it is discovered that the convergence of systems is faster using the control law based on error predictor than using the common one.     

Event‐Triggered Control for Multi‐Agent Systems with General Directed Topology and Time Delays

Recent years have witnessed a growing interest in event‐triggered strategies for coordination and cooperative control of multi‐agent systems. However, the most previous works and developments focus on the interactive network that has no communication delays. This paper deals with the consensus problem of an agent system with event‐triggered control strategy under communication time delays. We first propose a time delays system model, then present a novel event triggering function that not only avoids continuous communication but also excludes the Zeno behavior. Furthermore, we provide the consensus analysis using an inequality technique instead of the traditional linear matrix inequality method, and we demonstrate that the inter‐event times for each agent are strictly positive, which implies that the Zeno behavior can be excluded. Finally, simulation results show the effectiveness of the proposed approach and illustrate the correctness of the theoretical results.     

Distributed Observer‐based Stabilization of Nonlinear Multi‐agent Systems with Sampled‐data Control

In this paper, the distributed observer‐based stabilization problem of multi‐agent systems under a directed graph is investigated. Distributed observer‐based control protocol with sampled‐data information is proposed. The dynamics of each agent contain a nonlinear part, which is supposed to be general Lipschitz. In order to stabilize the states of the whole network, all the nodes utilize the relative output estimation error at sampling instants and only a small fraction of nodes use the absolute output estimation error additionally. By virtue of the input‐to‐state stability (ISS) property and the Lyapunov stability theory, an algorithm to design the control gain matrix, observer gain matrix, coupling strength as well as the allowable sampling period are derived. The conditions are in the form of LMIs and algebraic inequality, which are simple in form and easy to verify. Some further discussions about the solvability of obtained linear matrix inequalities (LMIs) are also given. Lastly, an example is simulated to further validate the obtained results.     

Tracking Control for Stochastic Multi‐Agent Systems Based on Hybrid Event‐Triggered Mechanism

This paper deals with the leader‐following consensus for nonlinear stochastic multi‐agent systems. To save communication resources, a new centralized/distributed hybrid event‐triggered mechanism (HETM) is proposed for nonlinear multi‐agent systems. HETMs can be regarded as a synthesis of continuous event‐triggered mechanism and time‐driven mechanism, which can effectively avoid Zeno behavior. To model the multi‐agent systems under centralized HETM, the switched system method is applied. By utilizing the property of communication topology, low‐dimensional consensus conditions are obtained. For the distributed hybrid event‐triggered mechanism, due to the asynchronous event‐triggered instants, the time‐varying system method is applied. Meanwhile, the effect of network‐induced time‐delay on the consensus is also considered. To further reduce the computational resources by constantly testing whether the broadcast condition has been violated, self‐triggered implementations of the proposed event‐triggered communication protocols are also derived. A numerical example is given to show the effectiveness of the proposed method.     

Variable Structure Predefined‐Time Stabilization of Second‐Order Systems

A controller that stabilizes second‐order vector systems in predefined‐time is introduced in this paper. That is, for second‐order systems a controller is designed such that the trajectories reach the origin in a time defined in advance. The proposed controller is a variable structure controller that first drive the system trajectories to a linear manifold in predefined time and then drives the system trajectories to a non‐smooth manifold with the predefined‐time stability property, in predefined time also; this is done in order to avoid the differentiability problem that inherently appears when stabilizing high‐order systems in finite time under the block control principle technique. The proposal is applied to the predefined‐time exact tracking of fully actuated mechanical systems. As an example, the proposed solution is applied to a two‐link planar manipulator, and numerical simulations are conducted to show its performance.     

Consensus of Delayed Multi‐agent Systems via Intermittent Impulsive Control

A novel intermittent impulsive scheme is presented to realize consensus of multi‐agent systems with time‐varying delay in this paper because intermittent impulsive control may break through the limitation of upper bound of impulsive intervals in general impulsive control in our consensus scheme. Instead of activating all the time, we introduce the intermittent impulsive control approach into the delayed multi‐agent systems where the impulsive controller is only functioned in the control windows. Based on the algebraic graph theory, the Lyapunov stability theory, and Halanay inequality matrix theory, some adequate conditions are proposed to guarantee the consensus of delayed multi‐agent systems via pinning intermittent impulsive control. Simulation results are provided ultimately to verify the validity of the proposed control mechanism.     

“Kronecker Basis” Based Average Consensus Analyses for High‐Order Linear Multi‐Agent Systems with Multiple Time Delays

This paper investigates the average consensus for multi‐agent systems governed by high‐order linear dynamics with multiple time delays. Necessary and sufficient conditions for high‐order average consensus under balanced communication topology are provided by using a newly defined mathematical concept – the Kronecker basis. Furthermore, previous studies for average consensus governed by first‐order, or high‐order integrator can be regarded as special cases of our results. Simulation results are employed to demonstrate the effectiveness of our results for high‐order average consensus.