Fixed-time consensus tracking control of second-order multi-agent systems with inherent nonlinear dynamics via output feedback

Nonlinear Dynamics - This paper is devoted to the fixed-time consensus tracking control problem for a class of second-order nonlinear multi-agent systems. Firstly, a fixed-time consensus control...     

Bounded consensus tracking of second-order multi-agent systems using rectangular impulsive control

Nonlinear Dynamics - In this paper, the problem of bounded consensus tracking for second-order multi-agent systems is addressed with fixed and randomly switching directed topologies, wherein the...     

Leader-following second-order consensus in multi-agent systems with sampled data via pinning control

This paper studies the second-order consensus in multi-agent systems with sampled position and velocity data via pinning control. The distributed pinning consensus protocols with second-order dynamics are designed, where both sampled position and velocity data are employed. Necessary and sufficient conditions are derived for reaching second-order consensus by combining the algebraic graph theory and the analytical method. According to the obtained consensus criteria, the second-order leader-following consensus can be reached if and only if the sampling period, the coupling gain, and the pinning gains satisfy some derived algebraic inequalities. Moreover, it is found that second-order consensus in multi-agent systems cannot be reached with only sampled position data in the pinning controllers. Finally, the effectiveness and correctness of our theoretical findings are demonstrated by some numerical examples.     

Finite-time consensus of multi-agent systems driven by hyperbolic partial differential equations via boundary control

Applied Mathematics and Mechanics - The leaderless and leader-following finite-time consensus problems for multi-agent systems (MASs) described by first-order linear hyperbolic partial differential...     

Finite-time consensus of nonlinear multi-agent systems via impulsive time window theory: a two-stage control strategy

This paper concentrates on the finite-time consensus problem faced by nonlinear multi-agent systems (MASs) via impulsive time window theory with a two-stage control (TSC) strategy. The TSC strategy divides the whole control period into two parts: a variable impulsive control stage and a finite-time consensus control stage. Different from general single-stage control, TSC can dynamically adjust the time periods of impulsive control and finite-time control according to practical application requirements. Variable impulsive control is also discussed in this paper. Compared with the sampling based on traditional fixed impulsive theory, impulsive sampling in the TSC strategy occurs randomly within an impulsive time window and provides much more flexibility. In addition, a switching topology scheme is introduced in this paper to strengthen the stability of MASs. Finally, two numerical simulation examples (one leaderless case and one leader-following case) are used for the theoretical analysis.

     

Finite-time consensus of high-order heterogeneous multi-agent systems with mismatched disturbances and nonlinear dynamics

Nonlinear Dynamics - In this study, we investigate the finite-time consensus problem for a general class of high-order nonlinear heterogeneous multi-agent systems, for which not only the unknown...     

Observer-based adaptive consensus tracking control for nonlinear multi-agent systems with actuator hysteresis

Nonlinear Dynamics - This paper addresses the consensus tracking problem of a class of nonlinear multi-agent systems by using observer-based control. The systems are in output-feedback form with...     

Adaptive neural network consensus tracking control for uncertain multi-agent systems with predefined accuracy

Nonlinear Dynamics - This paper proposes the consensus tracking control problem for a class of uncertain nonlinear multi-agent systems. By using a group of nonnegative functions, an adaptive neural...     

Second-order consensus seeking in directed networks of multi-agent dynamical systems via generalized linear local interaction protocols

This paper focuses on the analytical study of final consensus convergence state of multi-agent dynamical systems by using a kind of generalized linear local interaction protocols. All the agents in the fixed directed network topology are governed by double-integrator dynamics. Almost all the existing linear local interaction consensus protocols can be considered as special cases of the present paper. By combining the algebraic graph theory and the matrix theory, some necessary and sufficient conditions are derived for reaching the second-order consensus. Moreover, the finial consensus convergence states of all agents are also be analytically determined. According to the obtained results, it is found that both the linear gains and the eigenvalues of the Laplacian matrix associated with the directed network topology play key roles in reaching consensus. Finally, the effectiveness and correctness of our theoretical findings are demonstrated by some numerical examples.     

Double event-triggered leader-following consensus and fault detection for Lipschitz nonlinear multi-agent systems via periodic sampling strategy

This paper considers the problem of leader-following consensus and fault detection for a class of multi-agent systems with Lipschitz nonlinear dynamics. To reduce the amount of redundant information and avoid checking triggering conditions continually, this paper proposes an efficient network framework with a double periodic event-triggered mechanism. Based on the proposed framework, an improved fault detection observer and a consensus controller are designed. Then, the original problem is converted into a set of stability problems with constraints. According to Lyapunov–Krasovskii theorem and the free-weighting matrix technique, sufficient conditions for solving these stability problems are derived in the form of bilinear matrix inequalities (BMIs). Further, to eliminate the nonlinear terms of BMI and obtain optimal performance, two iterative algorithms based on linear matrix inequalities (LMIs) are developed. Two simulation examples are provided to verify the practicality and validity of the theoretical results.

     

Leader-following consensus of nonlinear fractional-order multi-agent systems over directed networks

Nonlinear Dynamics - This paper investigates the leader-following consensus of nonlinear fractional-order multi-agent systems where the linear part is depicted by the general linear dynamics on...     

Consensus of second-order multi-agent systems with nonlinear dynamics and switching topology

This paper is concerned with the consensus problem in second-order multi-agent systems with nonlinear dynamics and switching topology. The switching rule is assumed to switch among a finite number of undirected graphs and be trajectory dependent. By using Lyapunov–Metzler inequalities, some easily checkable conditions are obtained to guarantee that consensus can be achieved by a state switching rule. Two examples are presented to illustrate the effectiveness of the obtained results.     

Consensus of second-order multi-agent systems with nonlinear dynamics and time delay

This paper aims at investigating the second-order consensus problem of the multi-agent systems with nonlinear dynamics. Since it is more difficult to obtain the velocity information compared with the position information in practical application, a very simple sufficient condition for updating the coupling gain of the velocity information exchange between each agent is firstly derived to achieve asymptotic consensus. Furthermore, communication delay of each agent is considered for velocity information exchange. The velocity signal from a virtual leader is introduced to reach the second-order consensus. All the above fundamental consensus criteria are guaranteed base on algebraic graph theory, matrix theory, and Lyapunov stability method. Two simulation examples are provided to demonstrate the effectiveness of the analytical results. The results obtained in this paper can be easily applied to various cases, which can facilitate practical designs for the second-order consensus.     

Asymptotical consensus of fractional-order multi-agent systems with current and delay states

In this paper, we study some new fractional-order multi-agent systems with current and delay states(FMASCD). Using the generalized Nyquist's stability criterion and Gerschgorin's circle theorem, we obtain the bounded input-bounded output(BIBO)stability and asymptotical consensus of the FMASCD under mild conditions. Moreover,we give some numerical examples to illustrate our main results.     

Adaptive consensus control of fractional multi-agent systems by distributed event-triggered strategy

Nonlinear Dynamics - In this paper, based on adaptive control, the consensus problem of fractional general linear multi-agent systems is studied. A new adaptive consensus control is designed and...     

Accelerated consensus to accurate average in multi-agent networks via state prediction

This paper considers the double-integrator consensus speeding up problem for multi-agent networks (MANs) asymptotically achieving distributed weighted average. First, basic theoretical analysis is carried out and several necessary and sufficient conditions are derived to ensure convergence to weighted average for both directed and undirected networks, but the convergence is generally slow. In order to improve the rate of convergence, an approach is proposed to accelerate consensus by utilizing a linear predictor to predict future node state on the basis of the current and outdated node state. The local iterative algorithm then becomes a convex weighted sum of the original consensus update iteration and the prediction, which allows for a significant increase in the rate of convergence towards weighted average consensus because redundant sates are bypassed. Additionally, the feasible region of mixing parameter and optimal mixing parameter are determined for undirected networks. It is worth pointing out that the accelerated framework has tapped the maximum potential to the utmost, from both the current and outdated state stored in the memory, to improve the rate of convergence without increasing the computational and memorial burden. Finally, a simulation example is provided to demonstrate the effectiveness of our theoretical results.