Hysteresis online identification approach for smart material actuators with different input signals and external disturbances

In this article, we present a fraction-order polynomial-modified Prandtl–Ishlinskii (FPMPI) and online infinite impulse response (OIIR) integrated model to describe the rate/load/temperature hystereses for smart material actuators. Hysteresis loops exhibit dynamic, asymmetric and saturate phenomena under different input rates, external loads and surrounding temperatures. It is difficult to apply a comprehensive model to accurately capture the hysteresis variation. The Hammerstein-based hysteresis offline identification study is conducted. It is found that the rate/load/temperature-dependent hysteresis cannot be described well via the offline approach, due to the system uncertainty and time-varying dynamics. By formulating the hysteresis modeling as an adaptive filtering problem, the OIIR filter and FPMPI integrated model is utilized for the rate/load/temperature-dependent hysteresis identification. Comparison of the online and offline identification results shows that the hysteresis online identification accuracies improve at least one order of magnitude, and two orders for some cases.