View source for Cascade Discrete-Continuous State Estimators for a Class of Monotone Systems

{{HTDB paper
| authors = Domitilla Del Vecchio and Richard M. Murray
| title = Cascade Discrete-Continuous State Estimators for a Class of Monotone Systems
| source = Submitted, 2005 IFAC World Congress
| year = 2004
| type = Conference Paper
| funding = NSF/Sensor
| url = http://www.cds.caltech.edu/~murray/preprints/dm05-ifac.pdf
| abstract = 
A cascade discrete-continuous state estimator design is presented for a class of monotone systems
with both continuous and discrete state evolution. The proposed estimator exploits the partial order preserved by
the system dynamics in order to satisfy two properties. First, its computation complexity scales with the number
of variables to be estimated instead of scaling with the size of the discrete state space. Second, a separation
principle holds: the continuous state estimation error is bounded by a monotonically decreasing function of the
discrete state estimation error, the latter one converging to zero. A multi-robot example is proposed.
| flags = 
| tag = dm05-ifac
| id = 2004r
}}