Dynamic Design Using the Kalman Filter for Flexible Systems With Epistemic Uncertainty

Most engineered systems have to exhibit a high degree of reliability and robustness. They are high in cost and complexity and often incorporate highly sophisticated materials, components, design and other technologies. Therefore, they face uncertainties in categories ranging from technical issues to market changes. This includes a wide range of epistemic uncertainties, such as demand or budget uncertainty; due to increasingly dynamic markets it has become important for systems to cope with these uncertainties. In this paper, a Kalman filter approach is applied to control the design as uncertainties are resolved in a discrete time frame. It is shown how the Kalman filter approach treats the design as a stochastic control problem, in which the design is controlled throughout its lifecycle to compensate for sources of epistemic uncertainty, as the uncertainties are resolved. The proposed method is applicable to flexible systems where changing the design is possible. A design framework is proposed encompassing a set of definitions, metrics, the methodology, and a case study of a spaceborne system.