State estimation of Two -Phase Reactor Condenser System with Recycle using multi -rate Unscented Kalman Filter

This paper delves into the pivotal role played by state estimation in advancing control strategies tailored for nonlinear models. While existing methods primarily focus on systems governed by Ordinary Differential Equations, this study assesses the effectiveness of the multi -rate Differential Algebraic Equation-based Unscented Kalman Filter for a Two -Phase Reactor Condenser System with Recycle. Differential algebraic equations incorporate a fusion of differential and algebraic equations, making them well -suited for a broader range of systems characterized by constraints or inter-variable dependencies. The performance of the multi -rate differential algebraic equation-based unscented Kalman filter is examined under various scenarios involving regularly sampled multi -rate data, encompassing measurements taken at varying intervals. The Mean Squared Error metric is employed to gauge the efficacy of state estimation using the multi -rate differential algebraic equation-based unscented Kalman filter on the two-phase reactor condenser system.