Practical control problems often deal with parameter-varying uncertain systems that can be described by a first-orderplus-delay (FOPD) model. In this paper, a new approach to design gain-scheduled robust linear parameter varying (LPV)propotional–intergral derivative controllers with pole placement constraints through linear matrix inequalities (LMI) regionsis proposed. The controller structure includes a Smith Predictor (SP) to deal with the delays. System parameter variations aremeasured online and used to schedule the controller and the SP. Although the known part of the delay is compensated withthe ‘delay scheduling’ SP, the proposed approach allows to consider uncertainty in the delay estimation. This uncertainty istaken into account in the controller design as an unstructured dynamic uncertainty. Finally, two applications are used toassess the proposed methodology: a simulated artificial example and a simulated physical system based on an open canalsystem used for irrigation purposes. Both applications are represented by FOPD models with large and variable delays as wellas parameters that depend on the operating conditions.