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This paper compares two different methods applied to adaptive control of a real multivariable laboratory system of three interconnected tanks. In first case, a controller based on polynomial methods was used. The second method is based on model predictive control (MPC) approach. Both methods are based on a same model of the controlled process. Both controllers were realized as self - tuning controllers with on - line recursive identification of an ARX model of the controlled process. Results of real-time experiments are also included and quality of control achieved by both methods is compared and discussed.