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Model based predictive control (MBPC) is an optimization-based approach that has been successfully applied to a wide variety of control problems. When MBPC is employed on nonlinear processes, the application of this typical linear controller is limited to relatively small operating regions. The accuracy of the model has significant effect on the performance of the closed loop system. Hence, the capabilities of MBPC will degrade as the operating level moves away from its original design level of operation. This paper presents an MPC algorithm which uses on-line simulation and rule-based control. The basic idea is the online simulation of the future behaviour of control system, by using a few control sequences and based on nonlinear analytical model equations. Finally, the simulations are used to obtain the 'optimal' control signal. These issues will be discussed and nonlinear modeling and control of a single-pass, concentric-tube, counter flow or parallel flow heat exchanger w ill be presented as an example.