Main description:

The book articulates a series of scientific and technological developments described in a didactic way.

The book shows a broad view of system identification in several contexts: Current cases of study are in different control methods.

Experimental results in different environments (availability of data and computer code to reproduce the experiments).

Transdisciplinary approaches and discussions for each chapter.

Innovation as part of the final cases of study: developments are already affecting the new big data of the digital age and the era of the advanced control.

Contents:

Introduction. Data driven model predictive control. Data driven identification for closed loop system. Data driven model validation for closed loop system. Data driven identification for nonlinear system. Data driven iterative tuning control. Data driven applications. Data driven subspace prediction control. Conclusions and outlook.