Abstract
Optimal sensor selection is the most important issue for state estimation in dynamic systems. The objective of sensor configuration is to identify the number of sensors to obtain the maximum amount of information on the states in a process. This chapter presents various methods for optimal configuration of sensors in linear and nonlinear dynamic systems. The methods discussed include the sensitivity index, singular value decomposition, principal component analysis, observability gramian-based quantification measures for linear systems, and empirical observability gramian-based metrics for nonlinear systems. These methods serve as useful tools for optimal configuration of sensors for state estimation in various engineering systems.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
