Control Problem For Multi-agent Systems Research Articles

Output feedback containment control of multi-agent systems with semi-Markovian switching topologies and input-bounded leaders

This paper investigates the containment control problem of multi-agent systems with semi-Markovian switching topologies. Different from the related works, this paper considers a more general case that the control inputs of leaders are nonzero, the sojourn time distributions of the semi-Markovian switching topologies are mode transition-dependent, and the states of agents are not measurable. Reduced-order observer-based control protocols are proposed, respectively, for two cases that the transition rates are completely known and partially unknown, which ensures that the containment of the multi-agent systems can be achieved in the mean square sense. Finally, simulation examples are given to illustrate the validity of the theoretical results.

Sampled-data based structural controllability of multi-agent systems with switching topology

This paper investigates the structural controllability problem for multi-agent systems with switching topology in a sampled-data setting, where each agent can obtain its neighbors’ state information at sampling instants. Based on the zero-order hold circuit, we show that the sampled-data general linear switched multi-agent system is structurally controllable if the union graph has a spanning tree. For sampled-data switched multi-agent systems, we prove that controllability property is preserved if an unsampled subsystem is controllable and the sampling time is not pathological. Our results show that the sampled-data based multi-agent systems with switching topology can be structurally controllable even if each of its subsystems is not controllable. A numerical example is presented to demonstrate the effectiveness of the proposed results.

Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights

Using Lyapunov first method instead of traditional Lyapunov second method, this paper focuses on studying the consensus tracking control problem of multi-agent systems (MASs) with time-varying delays and arbitrary adjacent weights under fixed topology and switching topology, respectively. We first give four equivalent criteria for MASs with fixed communication topology, where the positive stability of matrix [Formula: see text] ( L is the Laplacian matrix of [Formula: see text], B is the leader’s adjacency matrix) not only plays a key role as usual but also becomes an urgent and more complicated problem due to the introduction of negative weights in MASs. Second, for MASs with switching communication topology if the average dwell time of switching topology, the total activation time of stable subsystems and the upper bound of time delay satisfy some conditions, then MASs with all stable subsystems (partially stable subsystems) can achieve consensus tracking. Finally, simulations are given to demonstrate the effectiveness of our theoretical results.

Iterative learning control for nonlinear heterogeneous multi-agent systems with multiple leaders

This article investigates the iterative learning control problem for a class of nonlinear heterogeneous multi-agent systems. The main contribution of this article is to apply iterative learning control algorithm to the multi-agent systems with multiple leaders, and solve the containment control problem of multi-agent systems in the sense of iterative learning control stability. Based on the framework of communication topologies, distributed iterative learning controllers are designed. And when the iterative learning control laws are applied to the systems, the containment errors between the followers’ states and the convex hull spanned by the leaders’ states over a finite-time interval are bounded, and furthermore, the containment errors can converge to zero as the iteration index approaches to infinity in the absence of initial errors. A simulation example is finally constructed to verify the effectiveness of the theoretical method.

Event-Based Formation Control of Networked Multi-Agent Systems Using Complex Laplacian Under Directed Topology

In this letter, the formation control problem of multi-agent systems with directed communication graphs is considered. A novel distributed event-triggered approach, which involves complex Laplacian, is proposed to address the problem. The event condition depends on periodic samplings of agent states, which automatically eliminates the possibility of Zeno behavior. Then, it is shown that, under simple verifiable conditions, the proposed control strategy results in the desired formation of agents. Finally, the results are verified by numerical examples.

Fuzzy Adaptive Containment Control for Nonlinear Nonaffine Pure-Feedback Multiagent Systems

This article addresses the containment control problem of multiagent systems under directed topologies, where the model of each agent is an unknown nonlinear nonaffine pure-feedback dynamic, and at the same time, the outputs and their derivatives of the leaders are unknown. To avoid the complex design process with the recursive methods (i.e., backstepping and dynamic surface), each unknown higher order nonlinear dynamic is transformed into a simple high-order integral model with unknown affine nonlinear terms in the last-order dynamic at first. Then, the fuzzy logic systems and the fuzzy state observers are constructed to approximate the unknown affine nonlinear terms and the unknown transformed states. Finally, a novel fully distributed fuzzy adaptive containment control law is generated according to the state observers and the supervised control. The stability of the closed-loop system is analyzed in the Lyapunov sense and the containment errors converge to a small neighborhood of the origin. Simulation results show the feasibility and effectiveness of the proposed scheme.

H∞ Scaled Consensus for MASs With Mixed Time Delays and Disturbances via Observer-Based Output Feedback.

In this article, the H∞ scaled consensus control problem for multiagent systems in the presence of external disturbances and mixed time delays in both input and Lipschitz nonlinearity is investigated. First, a state observer is introduced for each agent based on the output information of the agent. Then, a scaled consensus protocol is proposed via a truncated predictor output-feedback method, which can deal with the input delay. The integral terms with the mixed time delays that are contained in the transformed systems are analyzed by using the Lyapunov-Krasovskii functionals method, and sufficient conditions are obtained to achieve scaled consensus with guaranteed H∞ performance. An iterative procedure is utilized to calculate the linear matrix inequality. By this, the feedback gain and observer gain are then designed. Finally, a simulation example is provided to illustrate the effectiveness of the theoretical results.

Cooperative attack tolerant tracking control for multi-agent system with a resilient switching scheme

This paper studies the cooperative attack tolerant tracking control problem for multi-agent systems under sensor attacks. A group of distributed adaptive state observers with a resilient switching scheme is proposed to reconstruct the states, then the tracking control strategy is designed based on the estimates. It is shown that both of the estimation and the attack tolerance control performances are ensured despite of multiple sensor attacks and the disturbances. Finally, the experimental results of networked multi-axis motion control show the effectiveness of the proposed method.

Bearing-Only Formation Tracking Control of Multi-Agent Systems With Local Reference Frames and Constant-Velocity Leaders

In this letter, the bearing-only formation tracking control problem of multi-agent systems modeled as double-integrators in local reference frames is investigated. The sensing topology among all agents is described by a multiply rooted undirected graph and the autonomous leaders associated with a common reference frame move with a constant velocity. The proposed control law for each follower depends merely on the relative bearings and relative orientations to its neighbors in its local reference frame. The orientation synchronization problem is first solved so that all orientations of the followers converge to that of the leaders. Then, a bearing-only controller is developed to achieve the desired moving formation. Finally, an example illustrates the effectiveness.

Optimal topology design and distributed formation control of multiagent systems with complex‐weights directed networks

SummaryIn this article, we consider the optimal topology design and distributed formation control problem of multiagent systems (MAS) with complex‐weighted directed topology. First, a framework is proposed to associate optimal topology of MAS to a constrained optimization problem with a complex Laplacian matrix, which is independent of the agent dynamics. The main contribution of the proposed approach compared with existing results is that the proposed approach does not require the calculation of the stabilizing matrix such that the closed‐loop system is asymptotically stable, and a unique set of complex weights that satisfy associated cooperative conditions can be chosen. Then, a distributed formation control protocol is proposed to enable all agents to achieve the control goal. Finally, some numerical example results are provided to demonstrate the effectiveness of the proposed scheme.

Pull-Based Event-Triggered Containment Control for Multiagent Systems With Active Leaders via Aperiodic Sampled-Data Transmission

In this article, the containment control problem of multiagent systems (MASs) with active leaders under a directed communication graph is addressed. A novel pull-based event-triggered protocol combined with aperiodic sampled-data mechanism is first presented, where each agent merely updates controller at its own triggering instants. Under the proposed control protocols, the information is only exchanged and calculated at the aperiodic sampling instants, therefore, it can reduce communication congestion and save computing resources. Furthermore, the Zeno behavior is naturally excluded because the trigger instants are in the set of aperiodic sampled instants. By virtue of the algebraic graph theory and Lyapunov stability analysis, it is shown that the active leaders can reach their desired states predefined arbitrarily and all followers are driven to the convex hull formed by the leaders. Finally, an illustrative example is given to validate the theoretical results and emphasize the advantages of the proposed protocols.

Semiglobal Tracking Cooperative Control for Multiagent Systems With Input Saturation: A Multiple Saturation Levels Framework

This article proposes a multiple saturation levels framework to investigate the semiglobal tracking cooperative control problem of multiagent systems with switching communication topologies. This problem is solving by proposing a switching parametric Lyapunov approach and constructing a three-layer nodes model with mirroring nodes to reduce the complexity of controller design in which control inputs for different layers of nodes are with different saturation levels. A metamorphic low-gain feedback consensus protocol is developed, based only on the interaction information of different nodes, to ensure that the states of the followers approach that of the leader, if the dwell time can be reasonably selected and the switching derived topologies have a directed spanning tree. Moreover, the protocol is extended to the derived topology that frequently contains a directed spanning tree. Simulations are presented to verify the effectiveness of the new design techniques.

Fixed‐time observer based adaptive neural network time‐varying formation tracking control for multi‐agent systems via minimal learning parameter approach

This study proposes a novel control scheme to investigate the time-varying formation tracking control problem for multi-agent systems with model uncertainties and the absence of leader's velocity measurements. For each agent, a novel fixed-time cascaded leader state observer (CLSO) without velocity measurements is first designed to reconstruct the states of the leader. Radial basis function neural networks (RBFNNs) are adopted to deal with the model uncertainties online. Taking the square of the norm of the NN weight vector as a newly developed adaptive parameter, a novel RBFNN-based adaptive control scheme with minimal learning-parameter approach and fixed-time CLSO is then constructed to tackle the time-varying formation tracking problem. The uniform ultimate boundedness property of the formation tracking error is guaranteed through Lyapunov stability analysis. Finally, two simulation scenario results demonstrate the effectiveness of the proposed formation tracking control scheme.

Event-triggered cooperative containment control for a class of uncertain non-identical networks

A practical event-triggered design method is developed for cooperative robust containment control problem of multi-agent systems with multiple leaders. The multi-agent systems discussed in this paper are essentially heterogeneous, and each follower is modeled by a integrator with the external disturbance. A containment error also has been expressed to ensure all the outputs of followers converge to the convex hull spanned by the outputs of the leaders. For the case that the undirected communication graph among followers is connected, a distributed containment compensator is designed based on the local state information of neighboring agents. Furthermore, a distributed output feedback controller is designed to solve the event-triggered containment control problem of the continuous-time multi-agent systems. Finally, a numerical example is given to verify the effectiveness of the main results.

Cooperative adaptive fault-tolerant control for multi-agent systems with deception attacks

The fault tolerant control problem for multi-agent systems with deception attacks and actuator faults is studied in this paper. Under deception attacks, the false data will be injected to communication channels, and change the transmittal signals. It is extremely difficult to ensure synchronization control of multi-agent systems with deception attacks and actuator bias faults by using the existing fault-tolerant control methods. A novel distributed adaptive fault tolerant controller is constructed in physical layer, and a distributed impulsive controller is proposed to deal with deception attacks in communication layer. It is proved that the proposed fault-tolerant controller guarantees the synchronization of multi-agent systems with deception attacks and actuator bias. Simulation results verify the effectiveness of the proposed method.

Formation control of non-holonomic multi-agent systems under relative measurements

This paper addresses a formation control problem for multi-agent systems with non-holonomic constraints under relative measurements. To overcome the issue of non-holonomic constraints, we design a feedback controller deriving rotational and translational motions according to formation error. A special form of formation error is employed here, which depends only on relative positions in a local frame. Hence, the designed controller is distributed and relative, meaning that only relative measurements of neighbors are used. Because a clique-based function is used, not an edge-based one, the best performance is yielded of all distributed, relative, gradient-based controllers. Moreover, we derive a necessary and sufficient condition of graphs under which a desired formation is achieved by such controllers. The proposed method is valid regardless of the dimension of the space, and thus it is applicable to not only unmanned ground vehicles (UGVs) but also unmanned aerial vehicles (UAVs). The effectiveness of the proposed method is demonstrated by simulations.

PI-Type Iterative Learning Consensus Control for Second-Order Hyperbolic Distributed Parameter Models Multi-Agent Systems

This paper considers the consensus control problem of multi-agent systems (MAS) with second-order hyperbolic distributed parameter models. Based on the framework of network topologies, a PI-type iterative learning control protocol is proposed by using the nearest neighbor knowledge. Using Gronwall inequality, a sufficient condition for the convergence of the consensus errors with respect to the iteration index is obtained. Finally, the validity of the proposed method is verified by two numerical examples.

Bearing-based formation manoeuvring control of multi-agent systems with constant communication delays

This paper investigates the bearing-based formation manoeuvring control problem of multi-agent systems with constant communication delays. Leaders move with time-varying velocities, and followers aim to track leaders' motion and form a bearing-defined moving desired formation. A dynamic controller for each follower is developed based on its position, velocity, its neighbours' position, velocity, acceleration. The motion information of neighbours is obtained via communication, and communication delays are taken into account. Then a rigorous proof is provided to show that tracking errors of the neutral-type system are globally uniformly ultimately bounded. Finally, simulation results are presented to illustrate the effectiveness.

Distributed Synchronization Control With Signal Transmission Delay and Its Applications to Genetic Regulatory Networks

This paper investigates the adaptive distributed synchronization control problem of multi-agent systems, where the information transmission in the network is subject to unknown constant signal transmission delay. Firstly, an adaptive distributed control scheme is designed for a class of certain multi-agent systems to guarantee the synchronization among all agents is achieved. In the scheme, the unknown constant delay can be estimated online. Furthermore, compared with some existing works where some global information are required to design the controllers for the agents, the scheme proposed in our paper does not need the global information. By algebraic graph theory with Lyapunov stability theory, the whole closed-loop system stability analysis is provided. Then, the method is extended to a class of uncertain nonlinear MASs. Finally, genetic regulatory networks (GRNs) are used to show the effectiveness of the proposed design scheme.

Consensus Control of Multi-Agent Systems With Two-Way Switching Directed Topology

Abstract In this paper, a novel control protocol method is developed to solve distributed consensus control problems for multi-agent systems with switching directed topologies. Because of the external disturbance, the information cannot transmit completely so that the proposition of two-way topology is necessary. Besides, the external disturbance is considered naturally and we give a control protocol and parameters of noise intensity function in this paper. Furthermore, an example is given to support the proposed theorem. Finally, the simulation results prove the correctness of the theory.