Distributed Adaptive Leader-following control for multi-agent multi-degree manipulators with Finite-Time guarantees
A robust distributed adaptive leader-following control for multi-degree-of-freedom (multi-DOF) robot manipulator-type agents is proposed to guarantee finite-time convergence for leader-following tracking and parameter estimation via agent-based estimation and control algorithms. The dynamics of...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.usm.my/30477/1/IEEE_CONFERENCE.pdf http://eprints.usm.my/30477/ |
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| Summary: | A robust distributed adaptive leader-following
control for multi-degree-of-freedom (multi-DOF) robot
manipulator-type agents is proposed to guarantee finite-time
convergence for leader-following tracking and parameter
estimation via agent-based estimation and control algorithms.
The dynamics of each manipulator agent system of n degrees
including the leader agent are assumed unknown. For a
specific leader-following network Laplacian, the agents’
position, velocity and some switched control information can
be fed back to the communication network. In contrast to the
current multi-agent literature for robotic manipulators, the
proposed approach does not require a priori information of the
leader’s joint velocity and acceleration to be available to all
agents due to the use of agent-based robust adaptive control
elements. Due to the multi-DOF character of each agent,
matrix theoretical results related to M-matrix theory used for
multi-agent systems needs to be extended to the multi-degree
context in contrast to recent scalar double integrator results.
A simulation example of two-degree of freedom manipulators
exemplifies the effectiveness of the approach. |
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