Risk-Aware Particle Filtering For State Estimation In Recirculating Aquaculture Systems
Published in The 56th Asilomar Conference on Signals, Systems, and Computers, 2022
Recommended citation: J. Cardenas-Cartagena, M. Elnourani, B. Beferull-Lozano, and D. Romero, “Risk- Aware Particle Filtering For State Estimation In Recirculating Aquaculture Systems ,” in the 56th Asilomar Conference on Signals, Systems, and Computers, USA, 2022. TBA
We design a sequential non-linear risk-aware estimator based on particle filtering to compute estimates and approximate the system state posterior distribution. For this purpose, we consider the risk given by the expected variance of the squared error between the system state and the estimate conditioned on the observations. We compare the proposed estimator with existing risk-neutral estimators in terms of error variance, mean squared error, and execution time per iteration. The comparison is carried out using a simulation of a Recirculating Aquaculture System, a case study for non-linear critical systems, where the performance in estimation for low probability events becomes an important aspect. Our simulation results demonstrate a competitive estimation performance while ensuring a lower risk.