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Reduced-order observer-based robust leader-following control of heterogeneous discrete-time multi-agent systems with system uncertainties
- Source :
- Applied Intelligence. 50:1794-1812
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- In this paper, the leader-following control of heterogeneous discrete-time multi-agent systems (HD_MASs) in the presence of system uncertainties under directed topology is addressed. It aims to achieve reference tracking, disturbance rejection and robust control while the references and disturbances are generated by an autonomous exosystem. In practice, these agents are often different types of devices, thus they have different internal dynamics. Moreover, it is difficult to measure all states of each aircraft due to high cost or technical limitation. In this case, a novel leader-following output consensus problem is formulated and solved in this paper. Firstly, an appropriate linear transformation is proposed to divide the state information of each agent into measurable and unmeasurable parts. Then the reduced-order observer is designed only for unmeasurable parts. Based on the designed observer, the distributed feedback controller is proposed such that the outputs of all followers reach the same trajectory with the leader. In light of the internal model principle and discrete-time algebraic Riccati equation, the robust leader-following consensus of HD_MASs is achieved. Furthermore, this paper extends the results to continuous-time multi-agent systems. Finally, several simulation experiments are presented to verify the effectiveness of the theoretical results.
- Subjects :
- Observer (quantum physics)
Computer science
Multi-agent system
Internal model
02 engineering and technology
Algebraic Riccati equation
Discrete time and continuous time
Consensus
Artificial Intelligence
Control theory
0202 electrical engineering, electronic engineering, information engineering
Trajectory
020201 artificial intelligence & image processing
Robust control
Subjects
Details
- ISSN :
- 15737497 and 0924669X
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- Applied Intelligence
- Accession number :
- edsair.doi...........d7b60799a515d7f7bd26547e0b048bd5
- Full Text :
- https://doi.org/10.1007/s10489-019-01553-x