Prescribed Performance-Based Consensus of Nonlinear Multiagent Systems With Unknown Control Directions and Switching Networks

This article studies the distributed adaptive failures compensation output-feedback consensus for a class of nonlinear multiagent systems (MASs) with multiactuator failures allowing unmatched redundancy under directed switching graphs. With estimated information of neighbors, a novel distributed reference generator is designed. To compensate the unmeasured state variables of each agent, a reduced-order dynamic gain filter is constructed. Based on the generator and filter, and using the recursive design method, a distributed adaptive protocol is designed, where the adaptive technique is used to compensate the actuator failures. The proposed scheme can significantly relax conditions on the communication graph, which allows the graph to be disconnected at any time instant. The number of introduced variables in the filter and its dimension is greatly reduced and, thus, reduces the numerical challenge. The output-feedback consensus for nonlinear MASs with actuator failures and possible unmatched actuator redundancy is addressed for the first time. The consensus error can converge to an arbitrarily small set not affected by actuator failures, and the resulting closed-loop system is semiglobally stable. Finally, simulation results are given to illustrate the effectiveness of the proposed method.

Fixed-time leader-following/containment consensus of nonlinear multi-agent systems based on event-triggered mechanism

The consensus problem of nonlinear multi-agent systems is studied in this paper, considering the semi-Markov switching topologies under DoS (denial-of-service) attacks. In this regard, an event-triggered mechanism is introduced for multi-agent systems under DoS attacks. Moreover, combining the semi-Markov topology with the event-triggered mechanism, a new consensus controller under DoS attacks is proposed. Furthermore, by choosing the Lyapunov–Krasovskii function and applying the matrix inequality technique, a sufficient and necessary condition is derived for the system stability as well as the state consensus. Subsequently, H∞ norm is proposed to enhance the performance of the multi-agent systems. Finally, a numerical example is provided to show the effectiveness and applicability of the proposed approach.

Adaptive consensus for high-order unknown nonlinear multi-agent systems with unknown control directions and switching topologies

This article investigates the leader-following consensus problem of discrete-time nonlinear multiagent systems (MASs) over fading channels. With the consideration of the transmission among followers maybe affected by the fading networks, the nonidentical fading channels model is constructed. To reduce the transmission network burden, the dynamical event-triggered mechanism (DETM) is developed. Different from most of existing event-triggered strategies, the threshold parameter in the developed dynamical event-triggering condition is dynamically adjusted according to a dynamic rule. Based on the DETM, a distributed consensus control protocol is designed under fading channels. Then, sufficient criteria are provided to ensure that MASs can achieve the leaser-following consensus, and satisfy the H∞ performance index in the presence of fading channels. The desired controller parameters can be derived in terms of solutions of matrix inequalities that are lightly solvable. In the end, simulation results show that the designed dynamical event transmission policy is capable of diminishing communication burden more promptly and effectively than some existing ones.

Distributed dynamic average consensus for nonlinear multi-agent systems in the presence of external disturbances over a directed graph

In this article, we design an adaptive leader–follower consensus controller for a class of nonlinear multiagent systems in the presence of time-varying asymmetric output constraints and unknown control directions. A new state transformation approach is introduced for each agent to transform the output into an equivalent unconstrained state. An adaptive neural network-based backstepping control method and a Nussbaum function approach are integrated to design the leader–follower consensus controller that compensates for the unknown control directions and guarantees that the consensus tracking error converges to a small compact set. Examples are given to demonstrate the effectiveness of the proposed new design techniques.

Sampled-data leader-following consensus for nonlinear multi-agent systems with Markovian switching topologies and communication delay

This article investigates the consensus problem of nonlinear leader-following multi-agent systems (MASs) via adaptive impulsive control. A distributed impulsive controller is employed, in which an adaptive updating law in the discrete-time setting is designed for the impulsive gain. Moreover, in order to reduce the communication cost, a distributed self-triggered strategy is proposed to determine when the impulsive instant occurs. Some criteria are derived to guarantee consensus of leader-following MASs based on Lyapunov stability theory and algebraic Riccati equation. It is proved that the self-triggered impulsive sequence does not exhibit Zeno behaviour. Finally, an illustrative example is presented to empirically validate the effectiveness of the theoretical results.

This paper investigates the finite-time consensus tracking control problem of uncertain nonlinear multi-agent systems with unknown input saturation and unknown control directions. An adaptive fuzzy finite-time consensus control law is proposed by combining the fuzzy logic system, command filter, and finite-time control theory. Using the fuzzy logic systems, the uncertain nonlinear dynamics are approximated. Considering the command filter and backstepping control technique, the problem of the so-called “explosion of complexity” in the design of virtual control laws and adaptive updating laws is avoided. Meanwhile, the Nussbaum gain function method is applied to handle the unknown control directions and unknown input saturation problems. Based on the finite-time control theory and Lyapunov stability theory, it was found that all signals in the closed-loop system remained semi-global practical finite-time stable, and the tracking error could converge to a sufficiently small neighborhood of the origin in the finite time. In the end, simulation results were provided to verify the validity of the designed control law.

consensus problem of multi agent systems catch great attention in recent years. It is mainly due to its vast applications. Designing an appropriate control protocol that guarantees the desired agreement between the agents is the main purpose of the consensus problem. A linear matrix inequality (LMI)-based approach for the H_∞ consensus of leader-follower nonlinear multi-agent system (MAS) is proposed in this paper. In the proposed framework, fuzzy Lyuponov function (FLF) is chosen. Some slack matrices are introduced to decouple the Lyapunov matrices from the systems' one which provide more degrees of freedom to the consensus problem and leads to decrease the conservativeness. As a result, sufficient conditions for consensus problem are presented in terms of LMIs. Finally, In order to evaluate the validity and effectiveness of the proposed approach, a numerical example for consensus of nonlinear MAS with thirteen followers is solved and simulation results are provided. Obtained results demonstrate the solid validity and great effectiveness of the proposed approach.

This paper investigates the event-triggered prescribed-time bipartite consensus of nonlinear multi-agent systems. In order to significantly reduce the communication burden and energy consumption, a novel event-triggered mechanism and triggering condition are proposed. Then, a distributed prescribed-time control protocol is proposed for the discussed nonlinear multi-agent systems to achieve bipartite consensus within the prescribed time based on the event-triggered mechanism. Using the Lyapunov stability theory, the stability of the nonlinear multi-agent systems is proved and the corresponding sufficient conditions are obtained. Moreover, it is shown that the Zeno behavior can be excluded. Simulation results are presented to show the effectiveness of the theoretical results.

This paper investigates leaderless and leader-following consensus control problems for a group of Euler-Lagrange systems with unknown identical control directions under an undirected connected and time-invariant graph in the presence of parametric uncertainties. For both leaderless and leader-following consensus cases, distributed adaptive controllers are presented using the backstepping technique and a Nussbaum-type function. Moreover, these controllers are distributed in the sense that the controller design for each system only requires relative information between itself and its neighbors. The projection algorithm is applied to guarantee that the estimated parameters remain in some known bounded sets. Lyapunov stability analysis shows that the consensus errors converge to zero asymptotically. Simulation results on multiple two-link planar elbow manipulators are provided to illustrate the performance of the proposed algorithms.

Distributed impulsive consensus of nonlinear multi-agent systems with input saturation

In this brief, the authors study the fixed-time consensus problem for a class of first-order nonlinear multi-agent systems where the communication topologies are general directed. Both fixed-time tracking consensus and fixed-time leaderless consensus problems are investigated. For the leader-follower situation, the communication topology is only required to contain a directed spanning tree. As for the leaderless situation, the topology is required strongly connected. Simulations are finally provided to verify the effectiveness of the proposed algorithms.