The research addressed in this paper is focused on the estimation and control of a nonlinear industrial polymerization process. The majority of the available estimation techniques are not easy to implement on-line due to the intensive computations involved. Therefore, there is a need for an estimation technique that is simple, yet capable of handling multi-rate sampled data with variable measurement dead times. For the polymerization system under study, one such estimator is presented. Estimation is implemented within a nonlinear model predictive control algorithm (NLMPC). The combined estimator-controller is shown to display good set-point tracking and disturbance rejection properties via simulations involving some practical control problems.