This paper proposes a multiple-model solution to the problem of controlling an air heating fan subject to faults. These faults are modeled by means of an abnormal unknown airflow input rate which the nominal controller is not designed for. Moreover, the average temperature of the air flowing through the system, which can be seen as an offset on the corresponding dynamics, is (slowly) time-varying and highly dependent on the ambient temperature. The fault-tolerant control (FTC) method adopted makes use of set-valued observers (SVOs) to invalidate possible models of the system. Unlike classical fault detection, this approach does not rely on residuals to detect abnormal system operation. This fact allows to reduce the conservatism of the solution and enables a straightforward design from the faulty and nominal models of the plant. Moreover, the absolute distinguishability concept is used to derive input signals that bolster the detection of faults. Although SVOs require heavy real-time calculations that hinder its implementability in systems with low computational power, it is shown that the architecture of the FTC strategy proposed is highly parallelizable and, thus, may take advantage of standard multi-core processing units. Experimental results are presented.