This paper presents an estimation and control scheme for a class of industrial processes described by distributed parameter models with a moving radiant actuator. To overcome the lack of direct sensing alternatives for process state, a dual extended Kalman filter is established for estimating process status online based on a reduced process model and available output measurements. A distinct challenge that is addressed is the selection and construction of a suitable feedback signal from the distributed state estimate following the moving radiant actuator. The estimated status is then integrated into a rule-based feedback controller, which coordinates two manipulated variables of the moving radiant actuator to achieve the control objective. The two manipulated variables are the velocity and the radiant flux or power of the moving actuator. Both the estimation and feedback control strategies are demonstrated using computer simulations of one-dimensional distributed parameter models for an ultraviolet (UV) coating curing process involving a moving UV source. The results show that the proposed estimation and control schemes can significantly improve process quality and compensate for unknown disturbances on the target. (C) 2010 Elsevier Ltd. All rights reserved.