Distributed MPC based consensus for single-integrator multi-agent systems

Cheng, Zhaomeng; Fan, Menghua; Zhang, Haitao

doi:10.1016/j.isatra.2015.03.011

Cited by 34 publications

(10 citation statements)

References 32 publications

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“…Also, assume that the rough upper and lower bounds on the initial state and are 1 and −1, respectively. From (7), it can be seen that the minimal number of steps for direct calculation on 0 is 7. Therefore, in the scenario that there are enough output measurements over the horizon length = 7, condition (7)…”

Section: Optimal Bounds For Dfcmentioning

confidence: 99%

“…Various protocols are designed to achieve such a goal, for example, the nearest-neighbor rule [3]. Moreover, it leads to a well-studied field in control theory, distributed consensus [3][4][5] which can be viewed as a special case of this DFC problem; some model predictive control (MPC) methods are proposed to solve the consensus problem [6][7][8]. When the observations of each node are noise-free, [2] shows that, instead of requiring asymptotic convergence, finite observations are enough to compute a predefined function.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Function Calculation over Noisy Networks

Zeng

Yang

Zhang³

et al. 2016

Mathematical Problems in Engineering

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Considering any connected network with unknown initial states for all nodes, the nearest-neighbor rule is utilized for each node to update its own state at every discrete-time step. Distributed function calculation problem is defined for one node to compute some function of the initial values of all the nodes based on its own observations. In this paper, taking into account uncertainties in the network and observations, an algorithm is proposed to compute and explicitly characterize the value of the function in question when the number of successive observations is large enough. While the number of successive observations is not large enough, we provide an approach to obtain the tightest possible bounds on such function by using linear programing optimization techniques. Simulations are provided to demonstrate the theoretical results.

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Section: Optimal Bounds For Dfcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Function Calculation over Noisy Networks

Zeng

Yang

Zhang³

et al. 2016

Mathematical Problems in Engineering

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“…Some pioneering works on this topic can be found in References and references therein. For example, many early studies focused on the relative simple systems including single‐integrator systems and double‐integrator systems . Since then, many efforts have been devoted to the more general linear MASs .…”

Section: Introductionmentioning

confidence: 99%

Fully distributed bipartite output consensus of heterogeneous linear multiagent systems based on event‐triggered transmission mechanism

Cai

2020

Intl J Robust & Nonlinear

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This study investigates the fully distributed bipartite output consensus issue of heterogeneous linear multiagent systems (HLMASs) based on event-triggered transmission mechanism. Both the cooperative interaction and the antagonistic interaction between neighbor agents are considered. A fully distributed bipartite compensator consisting of time-varying coupling gain and dynamic event-triggered mechanism is first proposed to estimate the leader's states. Different from the existing schemes, the proposed compensator is independent of any global information of the network topology, is capable of achieving intermittent communication between neighbors, and is applicable for the signed communication topology. Then the distributed output feedback control protocol is developed such that the fully distributed bipartite event-triggered output consensus problem can be achieved. Moreover, we extend the results in HLMASs without external disturbances to HLMASs with disturbances, which is more challenging in three cases (a) the disturbances are not available for measurement, (b) the disturbances suffered by each agent are heterogeneous, and (c) the disturbances are not required to be stable or bounded. It is proven that the proposed controllers fulfill the exclusion of Zeno behavior in two consensus problems. Finally, two examples are provided to illustrate the feasibility of the theoretical results. K E Y W O R D Sadaptive control, bipartite control, event-triggered control, external disturbances, heterogeneous multiagent systems, output consensus 1 Recent years have witnessed rapid development in distributed cooperative control of multiagent systems (MASs) due to its extensive applications such as energy internet, mobile robot, and unmanned aerial vehicle formation. 1-3 As one of the most basic and pivotal problems in the cooperative control, the distributed consensus control has received considerable attention from investigators. It aims at designing the distributed control scheme such that a set of agents reach an agreement on state or output. Some pioneering works on this topic can be found in References 4-12 and references therein. For example, many early studies focused on the relative simple systems including single-integrator systems 4,5 and double-integrator systems. 6,7 Since then, many efforts have been devoted to the more general linear MASs. 8,9 Note 3382 /journal/rnc Int J Robust Nonlinear Control. 2020;30:3382-3410.CAI et al. 3383that the aforementioned works are developed on homogeneous systems, that is, the system dynamics of all agents are the same. However, in many practical scenarios, the system dynamics are often different. In this regard, the output consensus problem of heterogeneous MASs is usually studied. Several typical results have been obtained (see References 10-12 and the references therein). From the review of the control protocols in above-mentioned works, it can be observed that continuous communication between each agent and its neighbors is required. However, in many real applications, each ...

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“…The study on fault‐tolerant controller of multiagent system has received attentions among researchers. A model predictive control scheme for multiagent systems with discrete‐time single‐integrator dynamics is studied in Reference 18. In Reference 19, The networked high‐order multiagent with time‐varying actuator faults is controlled by an adaptive fault‐tolerant fuzzy tracking controller.…”

Section: Introductionmentioning

confidence: 99%

Robust fault diagnosis and fault‐tolerant control for uncertain multiagent systems

Yao

2020

Intl J Robust & Nonlinear

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This article considers the problem of fault diagnosis and fault-tolerant control for uncertain multiagent systems. First, the multiagent system model with disturbances and uncertainty parameters is shown in the article. Then, a new robust adaptive observer based on relative estimation error is used to estimate actuator faults and the parameters of the observer can be obtained by solving the proposed linear matrix inequality. After the fault estimation information is obtained, a robust output feedback fault-tolerant control algorithm based on fault estimation is proposed and the condition that the controller parameters need to be satisfied is given. Finally, the multiagent system with four aircrafts is used as an example to further prove the effectiveness of the algorithm proposed in this article.

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Distributed MPC based consensus for single-integrator multi-agent systems

Cited by 34 publications

References 32 publications

Distributed Function Calculation over Noisy Networks

Distributed Function Calculation over Noisy Networks

Fully distributed bipartite output consensus of heterogeneous linear multiagent systems based on event‐triggered transmission mechanism

Robust fault diagnosis and fault‐tolerant control for uncertain multiagent systems

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