CODE 80291 ACADEMIC YEAR 2020/2021 CREDITS 6 cfu anno 1 INGEGNERIA GESTIONALE 8734 (LM-31) - SAVONA SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04 LANGUAGE Italian (English on demand) TEACHING LOCATION SAVONA SEMESTER 2° Semester TEACHING MATERIALS AULAWEB OVERVIEW The course presents the main estimation and identification techniques to be used in the context of complex dynamic systems analysis, forecasting and control. AIMS AND CONTENT AIMS AND LEARNING OUTCOMES The learning outcomes of the course refer to the capacity of: knowing the properties of an estimator; identifying the main features of an estimation problem as regards the characteristics of data and the features of a suitable estimator; designing the solution of an estimation problem, that is, defining the best estimator knowing the features of an identification problem; knowing the most important classes of identification models; designing the solution of an identification problem. PREREQUISITES The course prerequisites refer to basic elements of systems theory, statistics and optimization. TEACHING METHODS Aula lessons and laboratory exercises. SYLLABUS/CONTENT Estimation theory: parameter estimation (correctness, consistency and efficiency of the estimator), Cramer-Rao theorem, minimum variance estimation (UMVUE and BLUE estimators), maximum likelyhood estimation, linear estimation with measurement errors (least square estimation, Gauss Markov estimator). Bayesian estimation (minimum squared error estimation and linear minimum squared error estimation). Kalman filter. Identification techniques: definition of the parameter identification problem, model families (ARX, ARMAX, OE, ARXAR, BJ), MPE identification: convergence theorems, identification for ARX models (least squares identification), for ARMAX models and for ARXAR models, batch and iterative algorithms. RECOMMENDED READING/BIBLIOGRAPHY L. Ljung, "System Identification: Theory for the user", Prentice Hall (2nd Edition), 1999. S.M. Kay, "Fundamentals of Statistical Signal Processing: Estimation Theory", Prentice Hall, 1993. TEACHERS AND EXAM BOARD SIMONA SACONE Exam Board SIMONA SACONE (President) MICHELA ROBBA SILVIA SIRI (President Substitute) LESSONS Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The evaluation consists in an oral exam. ASSESSMENT METHODS During the exam the student has to present the main arguments of the course, to solve numerical exercises and to explain the theoretical notions necessary for their solution Exam schedule Data appello Orario Luogo Degree type Note 13/01/2021 14:00 SAVONA Orale 03/02/2021 14:00 SAVONA Orale 17/02/2021 14:00 SAVONA Orale 08/06/2021 14:00 SAVONA Orale 25/06/2021 14:00 SAVONA Orale 15/07/2021 14:00 SAVONA Orale 02/09/2021 14:00 SAVONA Orale