Modelling and Control for Heart Rate Regulation during Treadmill Exercise

This paper proposes a novel integrated approach for the identification and control of Hammerstein systems to achieve desired heart rate tracking performance for an automated treadmill system. The pseudo-random binary sequence input is employed to decouple the identification of dynamic linear part from static nonlinearity. The powerful e-insensitivity support vector regression is adopted to obtain sparse representations of the inversion of static nonlinearity in order to obtain an approximated linear model of the Hammerstein system. An H _infin controller is designed for the approximated linear model to achieve robust tracking performance. This new approach is applied to the design of a computer-controlled treadmill system for the regulation of heart rate during treadmill exercise. Minimizing deviations of heart rate from a preset profile is achieved by controlling the speed of the treadmill. Both conventional proportional-integral-derivative (PID) control and the proposed approaches have been employed for the controller design. The proposed algorithm achieves much better heart rate tracking performance