The Kalman-Yakubovich-Popov lemma for Pritchard-Salamon systems
Systems & Control Letters
Corrections to “The Kalman-Yakubovich-Popov lemma for Pritchard-Salamon systems”
Systems & Control Letters
On-Line Parameter Estimation for Infinite-Dimensional Dynamical Systems
SIAM Journal on Control and Optimization
Model Reference Adaptive Control of Distributed Parameter Systems
SIAM Journal on Control and Optimization
Hyperstability of Control Systems
Hyperstability of Control Systems
Lagrangian sensing: traffic estimation with mobile devices
ACC'09 Proceedings of the 2009 conference on American Control Conference
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This work establishes an abstract framework that considers the distributed filtering of spatially varying processes using a sensor network. It is assumed that the sensor network consists of groups of sensors, each of which provides a number of state measurements from sensing devices that are not necessarily identical and which only transmit their information to their own sensor group. A modification to the local spatially distributed filters provides the non-adaptive case of spatially distributed consensus filters which penalize the disagreement amongst themselves in a dynamic manner. A subsequent modification to this scheme incorporates the adaptation of the consensus gains in the disagreement terms of all local filters. Both the well-posedness of these two consensus spatially distributed filters and the convergence of the associated observation errors to zero in appropriate norms are presented. Their performance is demonstrated on three different examples of a diffusion partial differential equation with point measurements.