Adaptive control is enhanced by background estimation

To allow for simultaneous real-time identification of background as well as the parameters of an autoregressive moving average model with exogenous inputs (ARMAX model) during adaptive control, a floating identifier (FI) approach is developed which may be used with most recursive identification algorithms. This method separates input and output data into low- and high-frequency components. The high-frequency components are used to identify the ARMAX model parameters and the low-frequency components to identify background. This approach was evaluated in computer simulations and animal experiments comparing an adaptive controller coupled to the FI with the same controller coupled to two other standard least-squares identifiers. In the animal experiments, sodium nitroprusside was used to control mean arterial pressure of anesthetized dogs in the presence of background changes. Results show that with the FI, the controller performs satisfactorily, while with the other identifiers, it sometimes fails. It is concluded that the FI approach is useful when applying ARMAX-based adaptive controllers to systems in which a change in background is likely.