From model-based control to data-driven control: Survey, classification and perspective

This paper is a brief survey on the existing problems and challenges inherent in model-based control (MBC) theory, and some important issues in the analysis and design of data-driven control (DDC) methods are here reviewed and addressed. The necessity of data-driven control is discussed from the aspects of the history, the present, and the future of control theories and applications. The state of the art of the existing DDC methods and applications are presented with appropriate classifications and insights. The relationship between the MBC method and the DDC method, the differences among different DDC methods, and relevant topics in data-driven optimization and modeling are also highlighted. Finally, the perspective of DDC and associated research topics are briefly explored and discussed.