Configuration of sensor network with uncertain location of nodes for parameter estimation in distributed parameter systems.* *This work was supported by the Ministry of Science and Higher Education under grant No. N N519 2971 33.

Abstract A sensor location problem for monitoring network with stationary nodes used for estimating unknown parameters of distributed-parameter system is addressed. In particular, the situation is considered, when the actual spatial positions of sensor nodes at the experimentation stage may be uncertain to some extent and randomly fluctuate around some locations specified at the configuration stage. In the presented approach, some results from experimental design theory for dynamic systems with random regressors are extended for the purpose of configuring a sensor network. Then, a simple algorithm based on the notion of approximate near minimum from statistical learning theory is adapted to select the most informative sensor locations. The delineated approach is illustrated by numerical example on a sensor network design for a two-dimensional convective diffusion process.

[1]  Dharma P. Agrawal,et al.  Current Trends in Wireless Sensor Network Design , 2005, Int. J. Distributed Sens. Networks.

[2]  Christos G. Cassandras,et al.  Sensor Networks and Cooperative Control , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[3]  Arye Nehorai,et al.  Landmine detection and localization using chemical sensor array processing , 2000, IEEE Trans. Signal Process..

[4]  Arye Nehorai,et al.  Design of chemical sensor arrays for monitoring disposal sites on the ocean floor , 1998 .

[5]  D. Ucinski Optimal Selection of Measurement Locations for Parameter Estimation in Distributed Processes , 2000 .

[6]  Mani Srivastava,et al.  Overview of sensor networks , 2004 .

[7]  Deborah Estrin,et al.  Guest Editors' Introduction: Overview of Sensor Networks , 2004, Computer.

[8]  Mathukumalli Vidyasagar,et al.  Statistical learning theory and randomized algorithms for control , 1998 .

[9]  Carlos S. Kubrusly,et al.  Sensors and controllers location in distributed systems - A survey , 1985, Autom..

[10]  Mathukumalli Vidyasagar,et al.  Randomized algorithms for robust controller synthesis using statistical learning theory , 2001, Autom..

[11]  Marc M. J. van de Wal,et al.  A review of methods for input/output selection , 2001, Autom..

[12]  Bruno Sinopoli,et al.  Distributed control applications within sensor networks , 2003, Proc. IEEE.

[13]  G. Goodwin,et al.  Optimum experimental design for identification of distributed parameter systems , 1980 .

[14]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[15]  Ionel Michael Navon,et al.  Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography , 1998 .

[16]  Petter Ögren,et al.  Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment , 2004, IEEE Transactions on Automatic Control.

[17]  E. Rafajłowicz Optimal experiment design for identification of linear distributed-parameter systems: Frequency domain approach , 1983 .

[18]  Dacian N. Daescu,et al.  Adaptive observations in the context of 4D-Var data assimilation , 2004 .

[19]  Maciej Patan,et al.  Configuring A Sensor Network for Fault Detection in Distributed Parameter Systems , 2008, Int. J. Appl. Math. Comput. Sci..