Recursive parameter and state estimation for a mining industry process

In this paper we consider the problem of recursive state and parameter estimation of a nonlinear system. We propose an approach where we combine Particle Filter (for state estimation) and Recursive Least Squares (for parameter estimation) The class of nonlinear systems is motivated by a real process of the copper mining industry. The proposed approach is tested with real data.