Regression analysis constitutes an important tool for investigating the effect of explanatory
variables on response variables. When outliers and bias errors are present, the weighted …

Robust data reconciliation is an effective technique designed to minimize gross errors
drawbacks over estimated process variables. This work presents a review focusing on …

Owing to the effect of measurement noise and sudden changes in the power system, the
robustness of state estimation for power system becomes very important. The Unscented …

Data reconciliation has played a significant role in rectifying process data which can meet
the conservation laws in industrial processes. Generally, the actual measurements are often …

In this work, a comparative performance analysis of robust data reconciliation strategies is
presented. The study involves two procedures based on the biweight function and three …

Hydrogen produced by microorganisms has been considered as a potential solution for
sustainable hydrogen production for the future. In the current study, an advanced real-time …

In an industrial scenario, one can find measured data that do not satisfy the mass and
energy laws of conservation. This problem can be approached by applying data …

Simultaneous occurrence of gross errors (outliers/biases/drifts) in the measured signals, and
drifting disturbances/parameter variations affecting the system dynamics can lead to biased …

Hydrogen produced by microalgae is intensively researched as a potential alternative to
conventional energy sources. Scaling-up of the process is still an open issue, and to this …

Measurement errors inevitably exist amongst on-line measured data in steam turbine power
plants. Problematic steam turbine isentropic efficiencies and turbine expansion curves are …