Abstract
This paper considers consensus control of unknown nonlinear multi-agent systems with unknown disturbance under undirected networks. The expected output signal of the leader is not available to all subsystems, only some subsystems can obtain it, and other subsystems will obtain the output regulation error through the network connections. The critical contribution of this paper is to develop a new distributed adaptive control protocol and disturbance observer based on relative output information to achieve the consensus control objective of the subsystems. Since only the relative output information is used, the adaptive control protocol we proposed is distributed. Also, a new lemma is proposed for the first time to analyze the stability of the subsystems. Comparing to current results, the challenge exists in this paper is that the external disturbance is unknown and does not have explicit expression. Based on this, designing a disturbance observer based on relative output information to achieve consensus output regulation is the motivation of this paper. Different from the existing disturbance suppression methods, only the relative output information is used for disturbance suppression, and only the part of disturbance that affects the common trajectory will be suppressed. The stability analysis of the systems is carried out by using algebraic graph theory, Lyapunov function, and Barbalat lemma. The outcome of the paper is that all variables of the systems are bounded and the output regulation errors of the subsystems converge to zero asymptotically. Finally, a numerical simulation is given to demonstrate the effectiveness of the proposed method.
Highlights
As an important research direction in the field of artificial intelligence, multi-agent system has achieved remarkable achievements in economic, military, transportation, clinical medicine, architecture, aerospace and so on [1]–[7]
We present a new distributed adaptive protocol and a disturbance observer to achieve state consensus, which utilize the relative output information obtained from the neighboring subsystems and consider the high-order nonlinear terms
MAIN RESULTS To extract the internal dynamics of (1) with zi ∈ Rn−1, a state transformation is introduced for the subsystem i, and zi ∈ Rn−1 is given by zi xi,2:n b2:n b1 yi, (3)
Summary
As an important research direction in the field of artificial intelligence, multi-agent system has achieved remarkable achievements in economic, military, transportation, clinical medicine, architecture, aerospace and so on [1]–[7]. Q. Wang et al.: Distributed Adaptive Consensus Control and Disturbance Suppression of Unknown Nonlinear Multi-Agent Systems relationships between agents, and the rules for information exchange between agents. In [41], the containment of a linear multi-agent system with disturbance generated from heterogeneous nonlinear external systems is studied under the condition that the nonlinear function is global Lipschitz. We consider distributed adaptive consensus control and disturbance suppression of unknown nonlinear multi-agent systems. We present a new distributed adaptive protocol and a disturbance observer to achieve state consensus, which utilize the relative output information obtained from the neighboring subsystems and consider the high-order nonlinear terms.
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