Published December 2007 | Version Published
Book Section - Chapter Open

Change Sensor Topology When Needed: How to Efficiently Use System Resources in Control and Estimation Over Wireless Networks

Abstract

New control paradigms are needed for large networks of wireless sensors and actuators in order to efficiently utilize system resources. In this paper we consider when feedback control loops are formed locally to detect, monitor, and counteract disturbances that hit a plant at random instances in time and space. A sensor node that detects a disturbance dynamically forms a local multi-hop tree of sensors and fuse the data into a state estimate. It is shown that the optimal estimator over a sensor tree is given by a Kalman filter of certain structure. The tree is optimized such that the overall transmission energy is minimized but guarantees a specified level of estimation accuracy. A sensor network reconfiguration algorithm is presented that leads to a suboptimal solution and has low computational complexity. A linear control law based on the state estimate is applied and it is argued that it leads to a closed-loop control system that minimizes a quadratic cost function. The sensor network reconfiguration and the feedback control law are illustrated on an example.

Additional Information

© 2007 IEEE. Issue Date: 12-14 Dec. 2007; Date of Current Version: 21 January 2008. The work by L. Shi and R. M. Murray is supported in part by AFOSR grant FA9550-04-1-0169. The work by K. H. Johansson was supported by the Swedish Research Council and the Swedish Foundation for Strategic Research.

Attached Files

Published - Shi2007p8746Proceedings_Of_The_46Th_Ieee_Conference_On_Decision_And_Control_Vols_1-14.pdf

Files

Shi2007p8746Proceedings_Of_The_46Th_Ieee_Conference_On_Decision_And_Control_Vols_1-14.pdf

Additional details

Identifiers

Eprint ID
20699
Resolver ID
CaltechAUTHORS:20101105-135641397

Funding

Air Force Office of Scientific Research (AFOSR)
FA9550-04-1-0169
Swedish Research Council
Swedish Foundation for Strategic Research

Dates

Created
2010-11-08
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Updated
2021-11-09
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