RESEARCH ARTICLE
Directed spanning tree–based adaptive protocols for second-order consensus of multiagent systems
Zhiyong Yu,
Haijun Jiang,
Da Huang,
Cheng Hu,
Zhiyong Yu
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorCorresponding Author
Haijun Jiang
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Correspondence
Haijun Jiang, College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China.
Email: [email protected]
Search for more papers by this authorDa Huang
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorCheng Hu
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorZhiyong Yu,
Haijun Jiang,
Da Huang,
Cheng Hu,
Zhiyong Yu
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorCorresponding Author
Haijun Jiang
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Correspondence
Haijun Jiang, College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China.
Email: [email protected]
Search for more papers by this authorDa Huang
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorCheng Hu
College of Mathematics and System Sciences, Xinjiang University, Urumqi, China
Search for more papers by this authorSummary
This paper discusses the consensus problem of second-order multiagent systems with nonlinear dynamics. A directed spanning tree–based adaptive control protocol is developed, which overcomes the drawback that the spectrum of the Laplacian matrix must be known a priori. A scheme for reordering the nodes is proposed. Applying the developed method and the Lyapunov stability theory, some distributed adaptive laws are designed in the directed network. It is found that the consensus can be achieved by randomly choosing a directed spanning tree and using the developed distributed adaptive law. Finally, an example is presented to illustrate the theoretical analysis.
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