Observer-based formation control of heterogeneous multi-agent systems without velocity measurements

This paper studies time-varying output formation control for linear heterogeneous multi-agent systems (MASs) under signed graphs, employing an adaptive dynamic event-based approach. The signed graph framework is used to model agent interactions, encompassing both cooperative and antagonistic behaviours. Firstly, a data-driven learning algorithm is given for the estimation of the unknown leader system matrix. Secondly, for a single leader MAS, a distributed adaptive dynamic event-based bipartite compensator is designed to estimate the leader's state. This triggering function utilises the internal dynamic variable to dynamically adjust the threshold, ensuring fewer triggering instances compared to traditional static thresholds. Thirdly, a controller integrating the compensator and observer is developed to solve the time-varying output formation control problem for heterogeneous MASs with signed graphs under a single leader. Subsequently, the findings are extended to multi-leader MASs, providing a solution for the formation control problem in such scenarios. Finally, several illustrative examples are provided to validate the theoretical results.

This paper studies the multi-tracking control for high-order heterogeneous multi-agent systems under a directed acyclic graph. The authors first convert the multi-tracking control problem for multi-agent systems into the zero steady-state error control problem of some independent subsystems. Based on final-value theorem and Mason's rule, a sufficient condition for achieving the multi-tracking control is proposed. It explicitly reveals how the system dynamic and desired object dynamic jointly affect the multi-tracking control of heterogeneous multi-agent systems. Meanwhile, a new result on the steady-state error for multi-subnetworks is established. Moreover, the multi-tracking control for heterogeneous multi-agent systems with time delay is discussed. Some simulations are performed to illustrate the effectiveness of the theoretical results.

This article studies the robust model predictive control of heterogeneous multi-agent systems with polytopic uncertainties and time delay. Moreover, some constraints on the amplitude of the control inputs are considered for each agent. The proposed distributed controllers are designed as state feedback. The goal is to design the feedback gains such that the multiagent system achieves consensus in the presence of time-delay and model uncertainties. For this purpose, an optimization problem is proposed, and by using the constrained robust model predictive control and the appropriate Lyapunov–Krasovskii functional, sufficient conditions are obtained to solve the optimization problem through solving the linear matrix inequalities. In this regard, a theorem is presented, and it is proved that the consensus errors converge to zero. Finally, the effectiveness of the proposed method is illustrated using numerical simulations.

Adaptive output containment control of heterogeneous multi-agent systems with unknown leaders

This paper investigates the optimal couple-group consensus control (OCGCC) for heterogeneous multi-agent systems (HeMASs) with completely unknown dynamics. The agents in HeMASs are divided into two groups according to order differences. Meanwhile, heterogeneous systems are transformed into homogeneous ones by adding virtual velocities. Then, a novel data-driven distributed control protocol for HeMASs is proposed based on policy gradient reinforcement learning (RL). The proposed algorithm is implemented asynchronously, and is specifically designed to address the issue of computational imbalance caused by individual differences among participants. It achieves this by constructing an actor-critic (AC) framework. The system’s learning efficacy is optimized using offline data sets. The convergence and stability are ensured by applying functional analysis and the Lyapunov stability theory. Finally, the effectiveness of the proposed algorithm is confirmed by various simulation examples.

Based on event-triggered control (ETC) and pinning control methods, this paper explores the finite time dynamic consensus (FTDC) issue of heterogeneous multi-agent systems (HMASs) composed of first-order and second-order agents. Firstly, a novel control protocol is designed to realize the FTDC of the system. Compared with periodic sampling control, in order to further reduce the update frequency of the controller, a fully distributed ETC is proposed. When the state error between agents meets the event-triggered condition, the controller will be updated. With the introduction of pinning control, the range of pinning gain of the second-order agents is determined. Eventually, the Lyapunov stability theory is adopted for theoretical analysis, and the correctness of the conclusion is verified.KeywordsFinite time dynamic consensusEvent-triggered controlPinning controlHeterogeneous multi-agent systems

ABSTRACTThis paper considers the controllability problem for both continuous- and discrete-time linear heterogeneous multi-agent systems with directed and weighted communication topology. First, two kinds of neighbour-based control protocols based on the distributed protocol of first-order and second-order multi-agent systems are proposed, under which it is shown that a heterogeneous multi-agent system is controllable if the underlying communication topology is controllable. Then, under special leader selection, the result shows that the controllability of a heterogeneous multi-agent system is solely decided by its communication topology graph. Furthermore, some necessary and/or sufficient conditions are derived for controllability of communication topology from algebraic and graphical perspectives. Finally, simulation examples are presented to demonstrate the effectiveness of the theoretical results.

Containment control of heterogeneous multi-agent systems

Scaled consensus control of heterogeneous multi-agent systems with switching topologies

Semi-global bipartite fault-tolerant containment control framework on antagonistic communication networks is proposed in this article for heterogeneous multiagent systems (MASs) under the influence of input saturation and actuator faults. An observer is constructed to estimate the leaders' states on signed digraph, where the communication networks are antagonistic. A fully distributed virtual control approach is developed to acquire the containment trajectory. Based on the observer, a semi-global containment control method is developed to compensate for the detrimental impacts of both input saturation and actuator faults. Besides, the dynamics and state-space dimensions of the agents can be different. The proposed framework overcomes two drawbacks of the conventional containment control: 1) the containment trajectory is obtained under general antagonistic communication networks, which is more general in engineering applications and 2) both actuator faults and input saturation are solved for heterogeneous agents, which relaxes the limitation of homogeneous dynamics. Finally, a simulation example is conducted to test and verify the feasibility of the proposed method framework.

Finite-time group consensus via pinning control for heterogeneous multi-agent systems with disturbances by integral sliding mode

Cooperation control of heterogeneous multi-agent systems (MASs) with different fractional order subject to intermittent sampled-data transmission is investigated in this brief. Existing works considering MASs with multiple fractional order mainly focus on continuous input with frequency domain analysis and their results are thus based on sophisticated characteristic equations. Instead, inspired by the memory retention property of Caputo fractional derivative, heterogeneous experience-based fusion controllers are devised to handle the hereditary effect based on time domain analysis. The devised fusion controllers are composed of intermittent sampled data, which not only incorporate current available samplings but also include earlier experience of agents. In addition, the fusion controllers can successfully transform MASs with different fractional order into general discrete-time plants at sampling instants, and at the same time, ensure the asymptotical stability of sampling errors as well as controllers besides those sampling instants. Thereby, the achievement of consensus only relates to the connectivity of communication graph. Effectiveness of theoretical results is substantiated finally by numerical examples.

Distributed model reference adaptive containment control of heterogeneous multi-agent systems with unknown uncertainties and directed topologies

This paper investigates the adaptive fault-tolerant formation control scheme for heterogeneous multi-agent systems consisting of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) with actuator faults, parameter uncertainties and external disturbances under directed communication topology. Firstly, the dynamic models of UAVs and USVs are introduced, and a unified heterogeneous multi-agent system model with actuator faults is established. Then, a distributed fault-tolerant formation controller is proposed for the unified model of UAVs and USVs in the plane by using adaptive updating laws and radial basis function neural network. After that, a decentralized formation-tracking controller is designed for the altitude control system of UAVs. Based on the Lyapunov stability theory, it can be proved that the formation errors and tracking errors are uniformly ultimately bounded which means that the expected time-varying formation is achieved. Finally, a simulation study is given to demonstrate the effectiveness of the proposed scheme.

This study explores fault-tolerant consensus in leader–following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler–Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.