A partitioned model-based internal model control (PM-IMC) design strategy is proposed for a class of nonlinear systems that can be described by just-in-time learning (JITL) modeling technique. The PM-IMC scheme consists of a conventional IMC controller augmented by an auxiliary loop to account for nonlinearities in the system. Two alternative implementations of the JITL are discussed and compared via simulation studies of an industrial polymerization reactor and an isothermal reactor exhibiting inverse response. It is shown that PM-IMC using the database-updating JITL is more desirable owing to the relative case in collecting the process data required to construct its initial database, while achieving comparable control performance as that obtained by PM-IMC using the JITL with fixed-database, which requires process data collected over the entire operating region to construct its database. In addition, a comparison is made between PM-IMC and its linear counterpart. (c) 2007 Elsevier Ltd. All rights reserved.