Category:Optimum Experimental Design

This category contains all control problems for which the underlying mathematical model describes an optimum experimental design (OED) problem. The task in OED problems is to determine controls and sampling decisions (when to measure) that yield an experimental setting with favorable properties. One usually strives to minimize a function of the covariance matrix that describes the uncertainty in a follow-up parameter estimation problem. This powerful methodology allows thus to reduce the number of cumbersome experiments to aquire data.

Extensions

• The differential equations might depend on state-dependent switches.
• The variables may include boolean variables.
• The underlying process might be a multistage process.
• The dynamics might be unstable.
• There might be an underlying network topology.
• The sampling decisions (when to measure) are usually (re)formulated by means of an outer convexification.