The challenge of intelligent sensing of monitoring and control

Intelligent sensors offer new capabilities in process measurement. Traditional control and system theory models do not adequately consider the measurement uncertainty information and the nonperiodic sampling possible from intelligent sensors. A new modeling framework for systems exhibiting these irregular observations is introduced. The framework uses linear constraints and a variation of descriptor system models to represent relational dynamics and set-valued observation information. The use of the model framework for set-valued state estimation is illustrated