Carlo Novara is an Associate Professor at Politecnico di Torino, Italy. He holds a Ph.D. degree in Computer and System Engineering. His research interests include nonlinear and LPV system identification, filtering/estimation, time series prediction, nonlinear control, data-driven methods, Set Membership methods, sparse methods, and automotive, aerospace, biomedical and sustainable energy applications.Simone Formentin is a Tenure-track Assistant Professor at Politecnico di Milano, Italy. He obtained his Ph.D. degree in Information Technology. His research interests include machine learning and automatic control, with a focus on mechatronics and automotive applications.

• Chapter 1: IntroductionPart I: Data-driven modelingChapter 2: A kernel-based approach to supervised nonparametric identification of Wiener systemsChapter 3: Identification of a quasi-LPV model for wing-flutter analysis using machine-learning techniquesChapter 4: Experimental modeling of a web-winding machine: LPV approachesChapter 5: In situ identification of electrochemical impedance spectra for Li-ion batteries Part II: Data-driven filtering and controlChapter 6: Dynamic measurementChapter 7: Multivariable iterative learning control: analysis and designs for engineering applicationsChapter 8: Algorithms for data-driven H∞-norm estimationChapter 9: A comparative study of VRFT and set-membership data-driven controller design techniques: active suspension tuning caseChapter 10: Relative accuracy of two methods for approximating observed Fisher informationChapter 11: A hierarchical approach to data-driven LPV control design of constrained systemsChapter 12: Set membership fault detection for nonlinear dynamic systemsChapter 13: Robust data-driven control of systems with nonlinear distortions