Distributed Output-Feedback Tracking of Multiple Nonlinear Systems With Unmeasurable States
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 8519324 |
Pages (from-to) | 477-486 |
Number of pages | 10 |
Journal / Publication | IEEE Transactions on Systems, Man, and Cybernetics: Systems |
Volume | 51 |
Issue number | 1 |
Online published | 1 Nov 2018 |
Publication status | Published - Jan 2021 |
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Abstract
In this paper, we investigate the distributed output-feedback tracking problem of nonlinear multiagent systems (MASs) where nonlinear functions of agent dynamics depend on unmeasurable states. Most existing results on output-feedback control of nonlinear MASs are concerned with nonlinear agent dynamics in output canonical form in which the nonlinear functions of agent dynamics only depend on the measurable output. When the nonlinear functions of agent dynamics depend on unmeasurable states, the problem remains open due to the difficulties in constructing distributed observers. When the leader is only available to a small portion of followers in the directed communication topology, we establish relationship between the network topology and the design of the corresponding distributed reduced order observers. Furthermore, by developing a new distributed high-gain homogeneous domination design method, distributed observers, and controllers are designed to guarantee that the errors between the followers' outputs and the leader's output can be made arbitrarily small while keeping all the states of closed-loop system bounded. Finally, a numerical example is employed to illustrate the effectiveness of the proposed control scheme.
Research Area(s)
- Directed topology, Distributed high-again homogeneous domination, multiple nonlinear systems, Unmeasurable states
Citation Format(s)
Distributed Output-Feedback Tracking of Multiple Nonlinear Systems With Unmeasurable States. / Li, Wuquan; Liu, Lu; Feng, Gang.
In: IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 51, No. 1, 8519324, 01.2021, p. 477-486.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review