Recent advances in data-driven dynamics and control

With the rapid development of artificial intelligence, the data-driven methods have been extensively applied in the fields of machinery, power, civil engineering, transportation and other industries, such as fault diagnosis and prognosis. Whereas the data-driven based accurate dynamic modeling, system identification, and their applications in the design of engineering equipment and structures and health management for life-cycle process are still in the early stage. Currently, researches on nonlinear dynamics depend mainly on traditional methods of analysis. For the further advancement of the field of dynamics and control in the era of artificial intelligence, it is urgent to discover new knowledge representations and new predictions of complex dynamic laws from the observed data. The future research of dynamics and control must be driven by both the physical principles as well as data. This paper introduces some recent research work by our group in structural optimization, active vibration control, system identification, fault diagnosis and prognosis, and state identification of heart rate variability signal, by using data-driven methods.