Many industrial processes are in cascade configuration in which the material being processed goes through a sequence of processing units. In many cases, direct in-process measurements of the relevant variable are not available at all but at the last processing unit Surrogate or model based soft measurements in which the relevant in-process variables are inferred from other measurements would be useful in these situations. Models necessary for the surrogate measurements however, are often not accurately known. In this paper, we propose a control method in which the surrogate measurement models are adaptively calibrated and the surrogate measurements are used for in-process feedback. The control law is developed in the context of moisture content control for paper manufacturing via successive vacuum dewatering. A Lyapunov based algorithm is derived and proved. Simulation results show that the proposed control strategy can regulate the exiting moisture content of each box at the desired value.