Considered in this research is a framework for effective formation control of multirobot
systems in dynamic environments. The basic formation control involves two important
considerations: (1) Real-time trajectory generation algorithms for distributed control
based on nominal agent models, and (2) robust tracking of reference trajectories under
model uncertainties.
Proposed is a two-layer hierarchical architecture for collectivemotion control ofmultirobot
nonholonomic systems. It endows robotic systems with the ability to simultaneously
deal with multiple tasks and achieve typical complex formation missions, such as collisionfree
maneuvers in dynamic environments, tracking certain desired trajectories, forming
suitable patterns or geometrical shapes, and/or varying the pattern when necessary.
The study also addresses real-time formation tracking of reference trajectories under
the presence of model uncertainties and proposes robust control laws such that over each
time interval any tracking errors due to system uncertainties are driven down to zero prior to
the commencement of the subsequent computation segment. By considering a class of nonlinear
systems with favorable finite-time convergence characteristics, sufficient conditions
for exponential finite-time stability are established and then applied to distributed formation
tracking controls. This manifests in the settling time of the controlled system being finite
and no longer than the predefined reference trajectory segment computing time interval,
thus making tracking errors go to zero by the end of the time horizon over which a segment
of the reference trajectory is generated. This way the next segment of the reference trajectory is properly initialized to go into the trajectory computation algorithm. Consequently
this could lead to a guarantee of desired multi-robot motion evolution in spite of system
uncertainties.
To facilitate practical implementation, communication among multi-agent systems is
considered to enable the construction of distributed formation control. Instead of requiring
global communication among all robots, a distributed communication algorithm is employed
to eliminate redundant data propagation, thus reducing energy consumption and
improving network efficiency while maintaining connectivity to ensure the convergence of
formation control.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-05-7886 |
| Date | 2010 May 1900 |
| Creators | Zhang, Junjie |
| Contributors | Jayasuriya, Suhada |
| Source Sets | Texas A and M University |
| Language | English |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | application/pdf |
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